E-commerce is the market that already influences the presence and determines the future. Aimondo AG is committed exclusively to the mission-critical segments of this market, which can be influenced by intelligent software, and those which follow globally determined, always identical rules.
eCommerce offers customers unprecedented transparency. At a glance, the potential customer captures all important information and product prices. Loyalty to providers is the exception – only Amazon has so far managed to be the product search-engine for a large part of online buyers. You have to be aware of this, if you want to be successful in eCommerce. And online success is a must – because the sales channels are increasingly overlapping and beyond the product features, touch-points with the provider, satisfaction as well as customer relation-management decide on the long lasting success. In particular, the acquisition of new customers is decided on the basis of manageable criteria – and they can be decisively influenced with our services.
Aimondo AG focuses on product developments that combine the following characteristics:
(1) SaaS - Software as a Service,
(2) Cloud - all functions are performed in the cloud,
(3) Artificial Intelligence (AI) - advanced functions that perform services as "software robots“
(4) Machine Learning (ML) - as a subgroup of the AI, which serves as self-learning algorithm modules for the overall AI concept
(5) Blockchain - as an integrity and safety concept for sensitive functions
(6) Unlimited scalability
(7) Language independence
(8) Cross-industry or cross-segment (neither horizontal nor vertical but both)
Aimondo develops itself, licenses and assembles or acquires them.
In any case, an internationally important position is set as a goal.
The initial product is the Aimondo eCommerce model of Aimondo GmbH (Düsseldorf/Germany) for advanced "Dynamic Pricing" on self-defined Business Intelligence. DaaS (Data-as-a-Service) for the most imortant growth market worldwide, eCommerce.
To always offer the right prices for your products, you don't need to install complicated software. It is sufficient to create a file e.g. in standard CSV- or Excel-format. Samples can be found in the Aimondo customer section of the dashboard. There it is also defined how little data Aimondo needs.
The finished file of any size is loaded into the Aimondo system. An automatic preliminary check takes place. Thereafter product enquieries are distributed via the cloud, answers are obtained in the shortest possible time and results are analyzed. The system filters the important information from the large amount of data, calculates and retrieves the net result in CSV-format in accordance with the custom-defined pricing strategy.
The finished, carefully structured information can be called up and transferred manually or fully automatically into the clients systems. Done.
This is how success in e-commerce works today. Because the right prices are the most important criterion for sales and margins. The procedure can be used weekly, daily or several times a day. For the whole range or parts thereof. This makes it possible to plan and calculate the achievement of business goals.
Cost-effective and highly efficient.
Every online retailer knows his assortment. However, this often means that not all data is available in the best possible order. Aimondo takes what's there. A certain minimum is required to be able to deliver clear results - this minimum is flexible. While other data providers need a unique product number (GTIN or EAN) to be able to find something. For example, with Aimondo designations, descriptions, manufacturer numbers or even pictures are enough to be able to search and find.
Because in many cases, on platforms such as eBay or in competitor webshops, numerically unmistakable information is not available. Aimondo´s Artificial intelligence searches like a human being. Compares text, data, pictures... sees a connection to the price. Aimondo checks whether the supplier can deliver quickly or at all. The supplier's ratings are included in the weighting. As a 4 or 5-star provider, you don't have to compare yourself with someone who is disqualified by critical customer ratings. Or with 2nd choice, special items or other conspicuous features. And of course, delivery costs are a criterion that is taken into account. The entire context is researched.
In this way, all offers that can be found are analyzed. These sometimes huge amounts of data are compressed - just as Aimondo customers wish and brought into shape. As soon as a reasonably comparable result is available, the online retailer's price strategy is applied and the desired result delivered.
Qualified results are generated from the raw data. These are condensed into manageable results. Better, more reliable, much faster and at a tiny fraction of the cost a human would incur for comparable work.
The mixture of massive computing power, elegant database structure, cloud technology, artificial intelligence and machine learning algorithms add up to this unique process.
It is our daily business philosophy to create the best possible customer satisfaction through first-class results. Once this is achieved, the Aimondo customer is successful. And its success is reflected in the Aimondo Group by the fact that its financial strength becomes the waste-product of best performance. Smart.
Aimondo's customers are on the safe side. All function modules are located in the virtual space, The Cloud. On virtual computers in data centers that only provide the computing power needed to the second when needed. All this is fail-safe because it is in different networks and in different service centres.
There is no function that is not secured by an identical copy elsewhere. And there are no functions whose execution is not electronically monitored.
Even the central control of this network intelligence is doubled in real time and monitored by electronic permanent monitoring. And then, of course, there are the people in the team who are notified in case of malfunctions. Unobtrusive, unagitated - with the most modern means of advanced IT technology.
The - of course double backed up - database records not only store all system processes but also the huge amounts of data as search results. This means that it is always possible to trace what was searched for, found, analysed and presented as a result at a certain point in time.
Over time, these qualified product- and price-data build up a stock that links historical results with the present and shows future trends. Developments can be predicted with high precision on the basis of special algorithms. The text and image collection also nourishes knowledge pools which - combined with the latest generation of text editing systems - can automatically form the most qualified customer information and consulting results – fully automated in best human understandable quality. Often with much richer and more informative details than those provided by the producers.
In day-to-day business, Aimondo customers can rely on Aimondo to restore everything that has been processed at Aimondo in the event that a data recovery becomes necessary.
It goes without saying that Aimondo lets the data and program functions work and stores them physically separate from each other. Damage from accidents, natural disasters and other crises can be very limited and do not cause any permanent disadvantage.
Management data go far beyond dynamic pricing details. They are "high level" and paint the big picture. According to our interpretation, however, with the possibility of branching top-down to the detail level. Modern management knows no limits and a manager in the online industry usually has in-depth knowledge of products, processes and market conditions.
On the other hand, management data must be intuitive and clear in the statement without further explanation. The diversity of a leadership task leaves little time to identify with the thought processes of the software developers extensively. It is often difficult to understand programmers way of thinking in order to arrive at simple „overview insights“.
This knowledge has given rise to the management level of our control panel. And it has been tested again and again by laymen to bring out simplicity from complexity. It took almost a year for the first trial version to be tested as an @-version by student teams from different disciplines. And another six months to derive the first ß-version from it. Since July 2018 we can present a version 1.0. Meaningful, informative and easy to use. If you create an account on the working version of aimondo.com, you can explore it to your heart's content. Any suggestion is very welcome, we know that versions are only steps on the evolutionary path.
Success in the highly competitive e-commerce markets is primarily the result of having the most attractive offer in all respects. Therefore it is necessary to analyse competitor prices in connection with the clear objective of knowing the position of one's own offer in comparison to competitors.
Online providers are more and more attaching strategic value to supply monitoring and the resulting price intelligence technology. The e-commerce ecosystem is becoming increasingly dynamic, with competitors' price movements having a direct impact on the company's own sales figures. If an online provider uses price intelligence as the mainstay of its sales strategy, it is able to recognize price fluctuations of competitors and adjust its prices in order to determine the own market position.
It is almost as important as complete price information to know the context. Consequently it is of a very high value to see the own product in context as well as the offers of competitors.
Where does Aimondo get the competitor data from?
From platforms and from the websites of direct competitors.
It is standard at Aimondo GmbH to examine the major online-platforms such as primarily Amazon but also eBay, Google Shopping, Idealo and many national platforms in target countries. There Aimondo finds the most comprehensive information about the current competitive situation. And most importantly. Amazon has about 50% of all online purchases in the countries where Amazon operates. Tendency: still rising.
eBay also plays a very important role in many areas. Especially here it is an outstanding advantage that Aimondo finds the direct comparison-articles with high precision even without clear EAN or GTIN. Artificial intelligence enables this high degree of text-, meaning-, context- and pattern-recognition with its self-learning characteristics. It is important for the customers to know, that since Aimondo operates there was no single day on which the system was unable to analyze the offers from these platforms.
But of course, the competitors who are named as direct rivals of Aimondo customers are also specifically scrutinized. Their offerings can usually also be found on the platforms, but the general conditions and prices may vary.
One of the "iron rules" of all members of the Aimondo Group is an almost unconditional quest for maximum customer satisfaction. This philosophy sometimes results in a solution that deviates from the standard or is not yet included. Realizing this is a challenge that the development team is happy to meet.
If a company works with methods such as artificial intelligence, machine learning, SaaS, cloud-based infrastructure, etc., one can certainly assume that as far as possible all other procedures will be carried out without manual work. All Aimondo projects meet this expectation.
In e-commerce, it is particularly the case in large and powerful online shops that the quantity of items alone prohibits frequent price corrections over the range manually. Once the guidelines have been defined for single items or article groups, the rules apply fully automatically. All steps are prepared by the Aimondo team in such a way that the psychologically correct prices are shown. And of course all prices are calculated as low as necessary and as high as possible. This ensures that sales volume and margin are always in the best relationship to each other.
Controls take effect with special information - if, for example, a competitor excludes prices so clearly that a person from product management must be informed.
Otherwise, the parameters are defined in such a way that the bestsellers are researched frequently, the middle segment periodically appropriate and the marginal products "from time to time" and readjusted if necessary. These processes run fully automatically in a way that the computerized findings are made available as structured data "database ready".
For assortment sizes that have five or six digits, manual data maintenance would take far too long to keep pace with dynamic market movements. Large retailers like Amazon change their prices for quite some items up to 15 times a day. With Aimondo you can capture these dynamics and adapt your own offer. Fully automatic with automatic data transfer. You can only counter the market successfully if you are technologically at or above eye level with the market power of online giants in the long run.
Aimondo has the basic interface to easily dock other systems.
Since revenues in e-commerce are often very scarce, every percentage point margin is important. Especially when articles are approaching the end of their life cycle or have to go for seasonal reasons, a radical price cut was often prescribed in the past. With full automation and adaptation to the data of the stock management system, the sellout discount can be minimized. The price is gradually optimized to a target stock at a predefined point in time in such a way that the margin is reduced in the largest possible and smallest necessary steps in a way that a 0 stock is reliably reached and the previously earned price range is not ruined.
Articles that have so far led a rather inconspicuous shadowy existence but have the unrecognized potential to become a bestseller if they would only have had the right price, are identified with Aimondo. They are lifted out of the grey anonymity of a hard to sell product group by competitive information and the price structure. There they can enrich the good or best-seller list and thus expand the top range - one of the most lucrative and thus economically most important findings in the trade. With Aimondo technology this is also fully automatic.
And while we're thinking about efficiency and optimization, Aimondo technology can also provide companies with fully integrated system components for both online and offline trading. The open interface of Aimondo not only supplies the database of the online shop with information but also the POS system of the brick & mortar retail trade. Electronic shelf labels used there are operated with the latest correct prices, which follow the same or differently defined rules of the system. Fully integrated, without human intervention and with the reliability and low error rate that IT systems have ahead of humans.
US $ 39 billion has already been invested worldwide. Large technology companies dominate investments. Private equity and venture capital investments and acquisitions have tripled from 2013 to 2017 and machine learning as a sub-group of AI is becoming a key technology.
However: only a few companies use algorithms successfully so far. The rest is struggling with a lack of knowledge, talents and strategies.
The majority of current external investments (around 60%) go into machine learning (up to 7 billion dollars), other important fields are image recognition (2.5 billion to 3.5 billion dollars) and speech recognition (600 million to 900 million dollars). These are the results of the McKinsey Global Institute (MGI) study "Artificial intelligence: the next digital frontier".
How does the practice of successful implementation of an AI application look like in an example?
Thousands of colorful dots appear on the monitor, light up briefly and disappear again. The IT manager's screen is swarming and flickering. Each point represents information that a car parts manufacturer records on its machines. It is data that helps to avoid expensive mistakes. No one has to evaluate them. It's done by algorithms.
The parts produced here for decades have become increasingly precise, harder and cheaper. But precise, hard and inexpensive is no longer enough today. To stand up to new and old competitors, a manufacturer not only optimizes quality. It also needs to produce faster, minimize costs, and become more efficient overall. This group relies on artificial intelligence (AI) too. To the colorful dots.
150 employees ensure that the company is provided with artificial intelligence. The team around the head of IT has developed new networks that monitor the factories of the automotive supplier like a giant brain. It discovers mistakes that no engineer in the world can detect.
The machines are equipped with sensors that measure their speed and production speed, compare their temperature, vibration and even noise patterns to see if there is any indication of wear. Every day, the AI team engineers receive millions of data from over 10,000 machines: How strong are forces acting on which position of the part to be produced? What is the temperature of the lubricating oil in the machine?
The AI is constantly learning from new real-time data. It "knows" when everything functions normally and when not. Too many red dots on the screen, which appear at ever shorter intervals, indicate that danger threatens: one of the machines could soon stop. Long before that happens, a technician sets off.
AI is the most important technology of the decade
The company described here already practices, for which most companies are still preparing. Namely the integration of artificial intelligence into the business, into the production.
The advantages of the new technology are enormous. Monitoring factories and controlling vehicle fleets, settling invoices and managing financial portfolios or even entire largely digitized organizations - algorithms now do all this faster, cheaper and more precisely than humans.
AI can save costs, improve customer relationships, increase sales as well as profits. It is intended to optimize merchandise management, sales and supply chains.
"Artificial intelligence will become the most important technology in the next ten years," says Heinrich Müller, Managing Director of Aimondo GmbH in Düsseldorf. This statement is supported by the McKinsey management consultancy, which expects more than 3,500 billion dollars in added value from AI worldwide.
"We are still in the early stages of artificial intelligence development, but the major digital companies have invested heavily in these technologies," explains McKinsey. "Traditional companies should now also concentrate on the fields of application in which they can save costs and tap new sales potential with the help of artificial intelligence“.
The most important economic benefit of AI is that it clarifies predictions and often makes them financially feasible in the first place. What and where does the customer buy at what price? How are product trends developing? When does which machine break down? What will a person fall ill with and what can be initiated preventively against it?
One of the new magic formulas of efficient management is very simple: data plus AI equals added value.
AI can destroy a series of existing business models. When autonomously driven taxis conquer the streets – how many people still need their own car ? When robots learn to sew T-shirts - who needs supply chains to textile factories in Asia? When software controls financial portfolios - who commissions an asset manager? And if Artificial Intelligence can manage entire online shops and organize delivery processes, who needs the traditional chain of buyers, marketing department, SEO specialists, market researchers, price managers and merchandise management?
The path to the AI future is as complex as the potential is great. As is so often the case, Germany is strong in basic research. The German Research Center for Artificial Intelligence in Kaiserslautern is considered one of the most renowned in the field worldwide.
Germany now even wants to become "the world's leading location for AI" and the government has adopted a "national AI strategy". The European Union, in turn, wants to invest 1.5 billion euros in AI development by 2020.
But what is that compared to the $16 billion fund that the Chinese port city of Tianjin alone wants to provide for the development of an AI-industry?
While China and the USA are investing heavily in technology, European corporations and SMEs are still hesitant. Many entrepreneurs want to tackle AI projects. But only one in four companies is already in a starting position to implementing them.
Unclear operational goals, high implementation costs, data protection concerns and a lack of suitable personnel are slowing down development. Entrepreneurs sometimes have great ideas, but they don't know how to implement them.
The great opportunity for European industry and trade lies in the tailor-made application of AI and achieving the best solutions in individual sectors.
Google or Amazon had a lot of data, huge computers and clever programmers. European dealers, importers and manufacturers know everything about production processes and high-quality logistics chains. They have expertise. And all they need are brilliant ideas, courage and some money to make their AI business productive and valuable. As with the car parts manufacturer described above or as with Amazon.
AI helps to recognize forces and relevant patterns in the multitude of influences.
Secure Software that monitors individual tasks, even complex ones, and detects anomalies has been around for decades. But: The complexity of an entire market environment overtaxes conventional software. AI shows its strengths when there are no clear causalities: it recognizes connections that have not been noticed before.
Process optimization, information crawlers and IT-based automation have been around for a long time. But it is only through the use of the most modern and powerful AI tools that orders of magnitude can be achieved that had not even been achieved to some extent and that no one would have thought possible three or four years ago.
Before the use of the technology, the definition of the economic purpose stands. What is the goal? To reduce the high surpluses in the warehouse of certain goods as far as possible without major damage? Or increase the sales of certain article groups by X percent? To observe the market and recognize decisions about direction? Recognise the strategies of other manufacturers and reposition your own products and "fight" stronger? Re-balance margins to strengthen the balance sheet? Once the goals in online-marketing are clear, Aimondo can determine what data exists, which data is missing - and with what effort it is possible to obtain missing data and derive the right actions from it.
Hunt for valuable data
When using AI, the data is assigned three roles: In the first step they are pure training mass to build up the first algorithm. In the second step, data from everyday life ensure that the algorithm can do its work. And finally, feedback data helps to optimize it.
But how much data do you need if you want and need to succeed in the online market? What is of statistical interest, wasted knowledge - and which data is economically directly efficient? Any new record could be a waste of money for a company - if it is incomplete or incorrect. Both conditions are equally dangerous. Or the data is worth its weight in gold - if the AI is enabled to take much better actions or even beats its competitors out of the field.
Therefore, the use of AI is always a strategic decision, a task for top management.
This also includes bringing the entire company into line with the Kl strategy. Many departments find it difficult to give or explain their data. Usually, only a small elite of companies are concerned with AI, but the majority of employees are not.
Artificial intelligence becomes better the longer and more intensive it is trained. AI that doesn't study all the time will soon be out of date. But even the most diligent neural networks need people to look after them, experts who understand them.
Medium-sized companies in particular have a hard time hiring AI talent. They are rare and often expensive. It is easier to use tools of innovative AI specialists and to adapt them to your own needs or to modify your own systems so that they can handle the net results of the AI specialists.
Caution, false promises
There are solutions on the market with which AI will drive the productivity of successful companies in the coming years. However, if some providers or consultants claim that AI will soon be able to do everything and function at the push of a button, this is nothing more than money-cutting. IBM's widely advertised supercomputer Watson, for example, has been abandoned by several customers, including the cancer research center MD Anderson in Texas, which invested more than $60 million in Watson technology.
In September 2017, Rhön-Klinikum AG also announced its intention not to use Watson. Watson simply did not live up to expectations, they say. Other services, such as the x.ai scheduler or Google's Duplex conversation program, admit that people still step in when the software gets stuck. Aimondo also has developers on standby around the clock. And developers who constantly monitor results and find ways to turn new insights from Big Data into useful information.
As much work artificial intelligence may save, it takes people to judge and decide how the results of the algorithms are used. Clever employees who understand the technology and use it strategically. The more important artificial intelligence becomes in companies, the more important human intelligence becomes, which AI introduces and strategically uses for the best benefit of the company.
Artifitial Intelligence" (AI) sounds impressive - its use must be skilful and subordinate to the entrepreneurial goal. Usually the employment without external specialists is not meaningful - the occupation with the bases of core business is too far away. And labeling fraud in the form that somewhat more complex database tasks are solved and sold as AI can never be effective in the long run.
Aimondo was created as an external service provider for AI in the cloud and has added elements such as machine learning, number crunching to generate smart data from raw data. Thereafter the net results are then transferred to a high-performance database. The user specification for e-commerce was then optimized. Normally, a company that manufactures completely different products or is successful in trade cannot maintain this specialization in its own company in a meaningful way. It is much cheaper and more efficient to be obtained externally.
We would like to give entrepreneurs the following tips, which can have a valuable influence on directional decisions when introducing AI:
Clearly described, achievable and controllable target
A common mistake is to start with Al without first defining a concrete and quantifiable goal. In most cases, the initiative is arranged "top down". Consultants or speakers at congresses have often successfully promoted Kl projects on the executive floor. The top management is then convinced that several sensors have to be installed, data crawled and enormous amounts of data collected, which are evaluated by algorithms. This would be the way out of which processes would inevitably be optimized. As a rule: this is a waste of time, energy, motivation and money.
In the determination phase, top management should listen to their own team rather than to an external consultant. Often Al is not the solution for an overarching problem in a company. AI is only at the beginning and consultants are learning from the customer. Experiment at the expense of corporate customers is not uncommon. It is therefore advisable from experience and entrepreneurial logic alone to constantly compare one's own goals with the technical and organisational possibilities. Individual tasks can now be solved efficiently with the best AI, while having entire organizations operating with AI influence is more of a medium-term goal. One that has to be thought visionary, but is realized in reasonable steps.
As important as consulting competence is, Al's main focus is on technical know-how. It is therefore cheaper, more realistic and more concrete to seek advice where it can be implemented. Because a purely strategic advice is expensive and usually brings nothing.
In the first step, a good Al consultant analyses which data are already available and which are still missing for a sensible Al approach. It is realistic to check with which effort these data are to be collected, obtained or provided. And how they are then further processed, analysed and consolidated in a result-oriented manner in order to achieve the desired result quickly and reliably.
The right data
If the AI algorithm does not get enough, incomplete or even wrong information, the result will be fatally wrong. If, for example, half of the competitor data is missing, the result of an analysis will only ever be able to position the own product in the midfield - and thus the system as a whole - up to the total endangerment of results. Applied to everyday life in companies, this means: Any Al project that does not collect enough data and therefor can not not lead to the target will inevitably fail. Companies and consultants are often not really interested in explaining data and the type of data collection in logical detail, at least in principle - instead they refer to a trade secret. If this is the case, it all too often conceals a weak point, it is better to take a break and opt for transparency instead of risk.
Clear decision pro AI
Every existential project that can be solved in a complicated way must be a matter for the boss if it is to succeed. The employees from the specialist departments who have the necessary knowledge are generally highly paid and busy. Therefore, the willingness of middle management to use them for an additional Al project is often low. It is therefore important to ensure active support from the company management. Entrepreneurs must be aware that an Al-system cannot be bought off the shelf and get started immediately. You need the knowledge of the individual departments or specialists. Management and departments must cooperate closely.
Dynamic Pricing in online Retailing
With the rapidly increasing success of online shopping came the concept of dynamic pricing. This was to be expected, but has presented many shop operators with problems that are still unsolved today. Internet giants like Amazon have expanded their technological lead and created almost monopolistic structures. At the expense of smaller online shops and brick & mortar retailers.
Dynamic pricing is a strategy in which retailers change the price of a product based on information about the competition and data about the demand situation.
To do this, they need a great deal of information. You need to know the prices of competitors and their performance in context. In addition, the assessment and market position of competitors is important basic information. Customer price perception in relation to deliverability and costs also plays an important role, as it determines the volume and profit margin that can be achieved.
In the past static prices were the rule, it was easy to find out how much a competitor asked for his products and how to compete. This has changed radically.
The old strategy has given retailers little opportunity to influence profits. Today, with dynamic prices, profitability can be constantly optimized, even for simply comparable products such as pharmaceuticals, electronics and sporting goods.
There Have Always Been Changing Prices
The idea of dynamic pricing is by no means entirely new to the retail trade. It is something that has long been part of the daily business of many organizations. It is a tactic that should attract the customer's attention and has proved to be extremely successful so far.
Some Examples of How Dynamic Pricing has Influenced Different Economies:
The concept of "Happy Hours" in a bar has helped to win customers at times that were quite untypical for a visit to the gastronomy. Of course, beverage prices were lowered, which attracted many customers. That increased the company's sales during this time. It also increased the profit for this time of day. It proved so effective that most bars and pubs have now adopted it.
Or the stock market. It works on the basis of rising and falling share prices. Similar to the concept of dynamic pricing, the value of stocks is calculated taking into account initial conditions, demand and some other parameters. This includes news from and about the company and its economic situation. Thus, prices are adjusted to adequately assess the current situation.
Take air ticket prices, for example. Here it is very clear that they all fly on the same route. On weekends and Fridays you will notice that prices are higher than on normal weekdays outside business hours. The predictable demand determines very different prices within a week or day. If several airlines are active on the same route, price dynamics continue to gain in importance.
It is only natural to try to increase profits by controlling prices on the basis of demand directly related to those of the competition. However subtle, the same ideology is practiced in many industries.
What has Changed Today?
Dynamic pricing is only possible if you have all the data at hand „now“. Another important aspect is the analysis of the data using a user- or industry-defined algorithm that is adapted to the specific business model. Quantifiable results can only be obtained if, in addition to the costs, all variables and the context are taken into account and an exact price adjustment is made.
One might ask oneself: if all this has always been thought and implemented, why did online trading take so long?
Factors that have made high-performance dynamic pricing possible are high-performance computing power as well as the latest AI technologies that have only recently emerged. The concept of collecting, storing and analysing data paves the way to larger things. And of course, the model of trade giants like Amazon is putting so much pressure on other suppliers that they themselves are becoming much more active in order to survive in the competition, which in some cases threatens their very existence.
Concerns of Retailers
Existing algorithms are supplied with all available data. These are details concerning the product and the market situation. The resulting price determines the profit or loss collected with the product.
A foolproof algorithm can give accurate answers. However, not all dealers use these possibilities. You can see that such price changes also pose a risk. That's something no one likes to accept. Even a slight decline or increase in product costs has an impact on profitability and prospects of success. Many people think first and foremost that prices are due to competition. This is true - but a price reduction can also result in volume growth, which increases the bottom line. Or the previous offer is cheaper than absolutely necessary and can tolerate an upward price correction while maintaining the current situation. In this case, a price increase is directly relevant to the result. Because a 1% higher price means an average 7.4% higher margin (EBIT) for the product on the balance sheet.
This algorithm can easily be used by traders. Many are hesitant because they do not understand how it works. This is also the case after taking into account the prices of competitors. A complete knowledge of the market environment, including the ancillary conditions, is a prerequisite for this. Best data then. Aimondo explains to each customer in detail how the algorithm works and how it can be applied precisely to the goals and philosophy of the online retailer or the manufacturer.
And yet not every retailer applies dynamic pricing in a structured form. Many are still limited to manually viewing individual products and react ad hoc. For large assortments, only a relatively small core area is covered, the difference between them often varies, errors are human and the result is a loss of ground compared to the competition, even to the break-even threshold.
The Success of Amazon
Amazon has had great success applying dynamic prices to its products. Other retailers are still trying to beat Amazon in this area without being able to use similar technology. That's the main reason why Amazon does it better than the competition. Amazon has always managed to set prices in such a way that they are attractive enough. Attractive in connection with their own warehousing targets.
Dynamic pricing, coupled with a good user interface and customer service, has enabled Amazon to be at the forefront. This was only possible through the correct synchronization of e-commerce compared to omnichannel and brick & mortar trade. Without lending and without always being the cheapest.
Amazon needs two minutes to make a price change! And Amazon checks its own prices several times a day. The algorithm determines whether Amazon makes the cheapest offer on the market or can successfully push a higher price through. The formula cannot be wrong - after all, this is how the world's most valuable company was created in a very short time, several other distribution companies that have been established for decades had to close their doors during this time.
Dynamic Price Determination in the Implementation
Dynamic pricing is a five-level module. It must be implemented step by step to avoid losing money. These are five phases in which the price of the goods is determined on the basis of various factors.
(1) The first module is the longtail module. It is the price that is set when the product is launched. It plays a decisive role in the success or failure of the product. The price is essentially based on the base price, the price of the raw material, the directly attributable costs and the targeted profit margins. Success depends on the product itself and the awareness, which is achieved through marketing.
2. In the second stage, the price shall be increased or reduced according to demand. Both can have a negative or positive effect on the result. By reducing the price, there may ultimately be more buyers. At the same time, consumers can be prepared to pay more if they accept the overall scenario.
(3) The third level is the Key Value Identity Module (KVI). It depends on the price perception of the consumer. It has a great influence on sales. A product is sold by the shop whose prices are below the prices of the competitors. This is the phase in which a customer is either won or lost. The KVI and the price must be right, the right analysis of sufficiently qualified basic data from as many providers as possible. The right action derivations forms the key to success.
(4) The Competitive Response Module is the fourth level. Here, price adjustments are made on the basis of competitors' price schemes. By selling at a lower price than the competition, you increase the chances that the customer buys. Here, too, it is necessary to constantly know all offers of the competition - the offers of the known competitors as well as the advances of possible newcomers which is mostly found on platforms rather than shops.
(5) The Omnichannel module is the decision-making area where a thorough analysis should be carried out on all channels where you do business. This is the fifth phase in which coordination takes place via all online and offline channels. It helps to balance the price and to keep the dynamic pricing at a realizable value. For this it is necessary to have a clear price-strategy area according to the analysis procedure, in which the parameters for dynamic pricing are precisely adjusted to the totality of conditions and credibility requirements. Of course, inventory data and sales expectations or obligations must be taken into account as well. The decisive factor here is that the Artificial Intelligence of pricing knows the specifications of the management and thus the goals of the company applying them. Ultimately, it is not the machine but the human being that is decisive.
How to find the most important value elements (KVI)
The bestsellers have the highest value. These are goods that the trade buy and sell with certainty. The profit margin is usually based on these KVIs.
It is not easy to influence KVI's. If you look at the wide range of products, you can usually see that 80% of turnover is based on KVIs. The Pareto principle. However, the profit is only up to 50%. This discrepancy is the first indication that dynamic pricing primarily influences sales. And it is a sign that it makes a lot of sense to identify articles outside the top 20% that make it into the top-20%-league or contribute more to profits through their optimized margin with several percentage points of price increases.
Low prices will generate more customers - how customers make decisions
When a person finds a suitable product, it is something that reveals a lot. The person will have previously checked several products and offers. This information is collected and the dynamic pricing rules can be applied to other similar products in the same group.
This is one of the benefits and results of dynamic pricing algorithms too.
If the customer finds the desired product with a supplier at a reduced price, it is natural for him to make a purchase there. Provided the framework conditions such as delivery time or evaluation are right. This, of course, increases sales.
Problems with dynamic pricing
Although dynamic pricing is useful, there are some issues to consider when using it.
With the same products, which are available at two different prices, the majority of customers will buy where the price is lower. This dealer will increase sales. There is an imbalance in the market. This will continue until the next best prize is awarded. A spiral can be set in motion.
An economy in which there are two different prices will not see growth but redistribution.
If the price dynamics depend on the customer (terminal used, address, history, etc.), the system will lead to discrimination. You cannot have permanently different prices for the same product for two different customers. But that would be the case if buyer parameters were used.
The concentration on selected KVI within the own assortment will disadvantage other articles. With the decline in demand for non-KVI products, the customer will eventually benefit. However, retailers will suffer a loss - for example through avoidable promotion or season sales.
Retailers offering goods at higher prices in physical stores and lower prices in online stores also take a risk, as this convinces customers to buy in the online store and not in the physical one.
With the race for the most successful e-commerce company, dynamic prices and aggressive pricing cannot benefit all retailers or overall economic growth.
It is therefore of existential importance to ensure that dynamic pricing is used at an early stage, that the right information is available quickly and reliably and that the pricing parameters are defined with the utmost care. Then and only then do you have a chance of sustainable growth with healthy operating results.
If the products are goods offered by different companies at the same time, the visibility of the offer in search engines like Google or Bing decides about online success and failure.
As a knowledge established over many years, one can assume that potential customers visit almost exclusively the pages that appear on the first results page. You can even - leaving aside a few marginal percentages - limit it to customers perceiving the first three results. A good 80% only click on the first three results, which they consider to be the most relevant. The rest "atomizes".
And to quote the correct Pareto rule again and again: within the first three results, around 75% of people make their decision in favour of the first offer.
If we stick to the rules that largely determine online business for a moment, we can conclude that the first result found leads to a product search for around 2/3 of sales. This is in any case the market leadership in this product within the target market.
"Trade can be that simple," you might say. Looking at reality, the dominant search engine Google likes to show as first results those from the Google shopping channel. Which criteria are applied here is obvious - they are Google advertising partners or advertisers. Even Google's own Google shopping company is also an advertising customer of Google.
In addition, "sponsored" results - direct ads - are displayed high up. As a rule, Amazon can also be found in the top league as an advertising company and as an "organic result" too. Then Idealo, the manufacturers themselves, eBay and other platforms can be found. Hardly any normal dealer manages to get there without payment or commission. Unless the offer is so attractive in context due to the right price that the (price-) search engines cannot avoid it.
If we take all this into account as facts, the requirements for a successful product presentation on the net become clear:
1. the product characterisation must be unambiguously
2. the product description must be accurate and as complete as possible
3. the prize should be placed in the top 3 of the best offers
4. the product should be available, the delivery time should be short
5. the delivery costs must not make the product unavoidably more expensive
6. The supplier evaluation must be correct - i.e. at least 3.5 out of 5 possible points.
Are all six points met ? The success is already assured - because the product becomes visible. And only a product that is ever seen can be bought.
Does the offer even make it into the buy box of Amazon, eBay or the Google Shopping offer... well then the course is set for success. Contracts are pre-condition of course – at least for the time being.
Aimondo knows these mechanisms inside out. Therefore, Aimondo not only has the technology to extract data from all shopping channels, but also the levers to equip each channel with the optimal price so that the different costs and commissions are taken into account in the calculation. Because within a sales platform, competition is just as tough as in the search engine.
2017 will be remembered as the year of the final breakthrough of state-of-the-art cloud services, i.e. software-as-a-service for software vendors, and will reduce the list of market opportunities to a single rule:
No SaaS, no sales!
Even the most complex data machines move smoothly towards online operation.
Why do companies choose SaaS?
Everywhere we see companies developing into ultra-modern, exclusively SaaS-based, high-performance companies. The reasons for this are obvious. Because more than 80% of performance apps are hosted and controlled in the cloud, organizations can organize themselves so that their operations no longer depend on central legacy systems. This makes absolute sense, as SaaS benefits often allow significant financial savings.
As expected, the main beneficiaries are small and medium-sized enterprises, which have had the best growth forecasts since 2018 thanks to SaaS.
The affordable price of SaaS technology, coupled with the high computing power of cloud applications, helps to equip companies with a whole range of new applications and involve all parties involved in the administration and operational areas of these applications. SaaS applications are easy to use. As a result, management does not have to organise expensive training courses to enable employees to use them. Also, no special devices are required, as the data is completely online. These applications connect easily to a range of third-party applications and solutions, and typically have open API access that allows establishing custom connections. This in turn leads to further improvements in efficiency and significant cost savings at the same time.
In short, companies are shifting their activities to the cloud because:
1. it costs less than the legacy systems,
2. it reduces operating costs,
3. it enables consistent work processes to be maintained,
4. it allows cooperation in large, decentralized teams,
5. it saves time for setup and training,
6. it facilitates access to programs, data and results,
7. it is mobile-optimized and independent of used devices,
8. it becomes easier to couple applications with each other,
9. it reduces (or eliminates) the cost of updating, maintaining and backing up data; and
10. it keeps them always up to date with the latest developments.
A few facts and figures on cloud development (as of 2017):
- 33% of all major companies use more SaaS technology than in 2016, averaging 16 applications.
- 38% of all US companies now support jobs that are exclusively equipped with SaaS programs. In 2016 this was only 17%.
- >80% of all end users in the United States prefer SaaS applications for communication and organization - in 2016 this figure was 51%.
- According to the market research company Gartner, the SaaS market is estimated at almost US$ 60 billion for 2017, with further growth of 21% per year forecasted.
- Over the same period, cloud services are growing by 18.5% per year - they have already reached over US$ 260 billion by 2017. Turnover is expected to reach US$ 411 billion by 2020.
- Four of the world's leading technology companies have already committed their development and acquisition strategies to SaaS products - Microsoft, SAP, CA Technologies and IBM.
Aimondo relies exclusively on cloud-based SaaS applications paired with artificial intelligence and machine learning technology.
2017 was also the year in which software developers understood on a broad front that it makes little sense to develop systems that master a single process and thus do not even cover all the needs of a particular industry. Experts around the world agree that the days of vertical software are long gone, in favor of applications that everyone needs. SaaS is neither vertical nor horizontal. SaaS is much better than both, and that's what makes it successful.
SaaS applications are targeted, but not industry-specific; they are designed to integrate with a variety of solutions. Open API access for developers and intuitive front-end design for inexperienced users is no longer a luxury - it is an important criterion without which the use of a SaaS solution makes no sense. Well-known brands such as Salesforce, Shopify, Zendesk, Ultimate Software Group, and others that have practiced this basic model from the beginning of its development. And are now generating millions and billions in sales and corporate value.
SaaS is now so good and mature that it is called the XaaS (Everything-as-a-Service) model. This means that many vendors are using modern technologies to deliver cloud services. This ensures that almost every process can be carried out online and without installation. Some of the most successful providers also implemented pay-as-you-go models to adapt their services to the needs of different users. This reaches and extends the reach to customers who would definitely be out of their focus without these simple cloud systems. Sometimes innovative SaaS vendors go so far as to offer smaller but completely powerful packages as "Freemium" - for free. Customers can try all features and experience in a limited test how they like and use the new tool an way of working. In short, XaaS is the result of SaaS' efforts to unify product development with service delivery, quality assurance and engineering.
With XaaS, customers can change their subscription terms and update their accounts, add or remove features, products or services at any time, and rely on always-on disaster recovery plans for their sensitive data circulating in the cloud. The usability has become device-independent, as a rule any browser is sufficient. Information is made available at all locations and in all instances. Another advantage is the familiar navigation and minimalist design that brings the technology closer to inexperienced users.
SaaS is not the foundation advantage for the development of XaaS, but an integral part of a much larger service landscape. XaaS not only enables service delivery models in cloud computing, but also the provisioning of otherwise very complex calculations and functions that run in the background. The user only sees the result.
Aimondo is such a complex application that delivers finished results after data entry and takes care of all intermediate steps in the virtual space. And it is explorable through a complete Freemium package without risk. When used commercially, a pay-as-you-go pricing policy replaces the otherwise substantial investment decision associated with the provision of a number of resources.
In this context, the increasing importance of artificial intelligence (AI) and solutions for machine learning (ML) must be seen. More and more SaaS products are using these tools. One can be sure that this development has and will have a disruptive development with the providers of conventional software packages and individually programmed automation solutions. Also in the way we do business in general, the impact of SaaS applications will be felt - the early adaptors will take the greatest advantage of it.
As implementation costs decrease, more SaaS vendors and their customers benefit from the advantages of AI and ML algorithms. Data analysis is one of the key areas of SaaS technology and artificial intelligence. It will enable efficient processing of data volumes that were not possible a few years ago. This can lead to a real marketing revolution, as AI can be used creatively in areas such as dynamic pricing, automated A/B testing, intelligent chat bots or predictive analysis (and in many cases already is). It looks like machine learning could very soon become a battlefield for leading SaaS brands. Aimondo relies massively on AI and ML, works on an intelligent text editing solution for millions of product descriptions and refines the iterative methods of data collection intelligence every day.
Unlike legacy-based on-premise solutions, where everything depends on the product created, SaaS systems are flexible. They enable the user to combine functions and functionalities in many ways. More features, tools, widgets and layers are added daily, with developers inspired by customer needs.
From 2018, a number of obsolete product marketing strategies will most likely be replaced by new-age feature marketing strategies. All in the service of an efficient target group approach with a high focus on intensive customer loyalty. Systems become more flexible and open to all types of customization, allowing companies to build customized applications on a common basis and at a fraction of the price. Even better, open API architectures enable connectivity with minimal programming effort, which more or less means that any application can work in any software ecosystem.
Once the time for an upgrade has come, decision-makers are relieved from writing off previous investments in versions that are no longer required. They simply select exactly the functions they want and perform their own tasks.
As the developer of a modern SaaS system, Aimondo relies on highly interactive marketing that reaches an international audience in carefully selected markets. Aimondo makes itself visible through organic and paid advertisments, where specific functions are searched. Experience shows that a SaaS model generates far more organic traffic from day one than a conventional software- or service-provider.
Another important task of Aimondo is to emphasize the power and power of artificial intelligence and machine learning even more strongly from 2018 and to use both in advertising statements.
What is the benefit for the Aimondo customer in this case? The barriers and costs of the AI are substantially reduced, since it is based on data and generates its results as output of the algorithms by processing massive parts of data collected. The Aimondo Business Intelligence application is an almost ideal example of the efficiency of an entire industry. Information is processed that has never been stored in own local databases. Only summarized results are provided in own systems and stored there as a data reserve.
The annual growth rate of successful SaaS vendors is a constant 30%, which alone says enough about and why they are extremely popular with investors.
In contrast to 2013, when a SaaS workplace was the vague, undefined idea in less than 40% of US companies, a market of > 60% of companies has opened up since 2018. They are ready to outsource mission-critical tasks to the cloud and they are ready to pay for them.
Several SaaS software vendors have exceeded the target of one billion net worth and more. The trend continues. A number of venture capital firms have officially declared their intention to invest in SaaS technology, and these intentions are inspiring an influx of new ideas that will certainly change and improve the look of our software landscape. With the right sales teams and marketing strategies, no innovative SaaS provider will have to fight for the necessary funding from 2018 onwards. The financing explosion is very likely to take place in 2019 already.
Why is dynamic pricing important in e-commerce?
Dynamic pricing has become crucial to success in e-commerce, especially through automation. Unlike employees who have to physically change the prices for thousands of items in a store (and create new price tags if no electronic shelf labeling system is available), prices can be dynamically adjusted online with little effort.
Advantages of dynamic pricing for e-commerce companies are:
(1) Sell faster and more profitably
With the data available for dynamic price optimization, conversion rates can be improved and pricing carried out in such a way that conversion rates and margins are in good proportion to each other.
Paid advertising is ideal for testing and improving the price structure. Advertising forums like Google Shopping offer immediate feedback on how the market reacts to a redefined price. Impressions, click-throughs, conversion rates and margins can be measured and compared with advertising expenditures and optimized in a targeted manner.
Ability to adjust to competitive prices
79% of consumers say they are bargain hunters. 78% say they compare prices from different sources before buying. Therefore the adjustment of prices in the online business is particularly important, because the price comparison only takes a few seconds and is effortlessly possible.
E-commerce companies can flexibly adjust and pursue their pricing strategies through dynamic pricing. You can specifically control margins, sales and even market shares.
(3) Trend understanding
Industry trends can be better identified through dynamic pricing, leading to shorter response times. Amazon has used the information from large amounts of data and the understanding of trends by offering discounts on the most popular items within the categories. They have given consumers the impression that they offer the best prices for all product categories.
(4) More effective inventory management
Dynamic pricing allows you to react to changes in inventory. For example, if an item is running out, you can increase the price of the item slightly to seamlessly bridge the time until the next goods receipt and achieve higher margins at the same time. If you have bought too much from another item, discounts flexibly matched to the inventory can lead to a reduction in inventory. Dynamic pricing enables optimized warehousing while at the same time safeguarding margins. The link between the merchandise management system and Aimondo´s Dynamic Pricing allows piece-exact sales control at the best possible price in each case.
(5) Higher up-sell conversion rates
Even without competitive influence, Dynamic Pricing provides e-commerce companies with data on what their customers are willing to pay for certain items. This is a fine control that product managers can perform manually or using specially developed algorithms as a routine daily task in knowledge of the competitive situation - it is worthwhile. Some companies give better prices on an initial purchase and accept a loss to provoke an upsell. Knowing the data on how an item's pricing affects the up-sell conversion rate, they can determine the optimal pricing for both items.
Dynamic pricing strategies in online retail
Some of the largest retailers are testing different pricing strategies - some of which pose a risk to their image, others are largely neutral or positive. Often a combination of data is packed into formulas to determine the final price of an item. Some of these pricing strategies used include
Supply and demand vary by location.
As an e-commerce company, supply and demand can be distinguished by region. Looking at these factors, prices can be adjusted by country, state or city. If customers notice this and exchange information about it, this type of profit optimization can permanently damage a company's reputation.
Time-dependent dynamic pricing.
Time can also play a role in dynamic pricing. Remember how gas stations lower prices during the day, according to once established schemes, raise slightly at the end of the day, offer lower prices in the evening and demand maximum prices in the late evening or at night.
Which prices are offered by competitors for the same product? Companies can - if they have the right and complete information always up to date - ensure that their prices are always lower. Or they can increase their price if their competitors demand more for the same product.
How a customer behaves can influence pricing. For example, was a customer on the website three times and looked at the same product, can a small bonus encourage him to buy? This type of customer action to trigger rebates or price changes can be an excellent way to perform tests and derive rules from them. However, the resourcefulness of customers should not be underestimated here either. And once the rule is recognized and perhaps even published in forums, it is not good for the reputation and costs margin.
Customer data or device information can also be used to control dynamic prices. If a customer has completed a survey and indicates that he has a high income, this information can be used to calculate a higher price. The same applies when you determine that a customer is using an expensive end device. Here, too, there is a danger that this will be understood as publicity and discrimination.
Dynamic pricing allows a lot of creativity. While automation and machine learning ultimately lead to measurable growth, there are an almost infinite number of ways in which data can be used to influence prices. For the customer the fairest and the company the safest way is to know the entire market on a daily basis and to ensure a price strategy that is constant, predictable, non-discriminatory and at the same time both competitive and sustainably profitable despite all the dynamics.
Resumee: Dynamic pricing in eCommerce
Dynamic pricing is the most direct and useful tool in the e-commerce toolbox. And it is a logical step for companies that want to increase their sales and improve their conversion rates and margins.
The ability to achieve these goals through the use of analysis tools and sophisticated artificial intelligence algorithms gives companies that use this method a big advantage over their competitors.
Online price information for manufacturers and brand distributors (MAP monitoring)
Sales channels have become more complex. Experienced buyers compare prices and choices online and decide how, where and for how much money they will ultimately buy. At the same time, resellers are investing in technologies that enable them to spy on other merchants and turn the price spiral. This behavior undermines brand integrity, affects margins and, worse still, can significantly affect relationships with resellers.
It is not enough to monitor only the most important online shops and marketplaces in order to maintain the MAP (Minimum Advertised Price) policy. In practice, it is often found that websites such as Amazon are not the first to drop prices under the MAPs. Price comparisons with another supplier are almost always the first to lower the price of the product. This may well be a dealer whom the manufacturer does not even know. If the big retailers notice this and even violate the manufacturer's recommended retail price, you as a representative of the brand could be confronted with a big problem. Often brands do not understand the enormous impact e-commerce has on other distribution channels until it is too late. The Internet offers more sales opportunities, but also makes it easier for unauthorized sellers to break into a manufacturer's carefully structured distribution channels or brand sales.
Who is affected?
Articles of an average brand are sold on more than 77 domains. And on average, almost 23 percent of their products are sold below recommended retail prices. The average discount on products is 17 percent below the MAP. At 20.5%, consumer electronics brands have the highest average price infringement rate. In this industry, around 80 percent of dealers are not authorized by the manufacturer. Of these 80%, 3/4 are smaller retailers offering through other marketplaces - mostly Amazon, eBay or smaller price comparison platforms. The electronics industry is followed with 20 percent off the recommended retail prices for household goods. In contrast to the 77 online retailers of an average brand, the outdoor industry has the highest number of sellers with 210 average sellers per brand. But also tyres, tools, fashion, furniture or accessories are advertised very aggressively online.
Why it is important
When pricing is an aspect and not the basic of a business, authorized vendors of brands can be very sensitive. This has an enormous influence on otherwise productive discussions between the brand manufacturer or distributor and their trading partners. When new products and other important marketing considerations are no longer discussed, but the sales team of the brand is bombarded with price problems, constructive discussions derail. This leads to a situation in which the retailer buys and sells fewer products of the brand.
How to manage channel complexity
To control the growing complexity of today's distribution channels, brands rely on a MAP policy. The retailers authorized by the manufacturer agree to the guidelines, in return the manufacturer undertakes to enforce the published prices. This maintains the margin for the seller. Re-importers and unauthorized sellers are identified and their sources of supply blocked. The integrity of the brand is maintained, as are the margins of the sales partners.
Advantages of Aimondo MAP monitoring for
(a) the trade mark
1.) Protection of the premium character of the brand;
2.) Identification of unauthorized sellers and blocking of supply sources;
3.) Consistent pricing for all sellers (preventing the brand from becoming a commodity);
4.) More turnover because the "good" partners have more in stock.
(b) the retailer
1.) Protects the margin so that the product can be properly promoted and supported;
2.) More goods in stock, because they can remain competitive through the service without losing through the price;
3.) Eliminates unauthorized vendors, leaving the legitimate retailer with more revenue.
(c) the consumer
1.) Assures buyers to purchase genuine and not counterfeit products;
2.) Warranty and after-sales support;
3.) Learns to trust a brand and contributes to brand loyalty.
Which steps can help to set up MAP monitoring?
Any brand distributor and any manufacturer can take steps to retain or regain control. It's not complicated:
1.) Introduce a clear MAP policy. One that clearly describes what is not allowed when selling your products. Remember that coupons, non-public prices and other discount types are common among discerning sellers. An MAP directive must cover these scenarios - and make it clear that they are infringements.
2.) Monitor the entire web: Make sure you enforce pricing comprehensively. Brands must enforce MAP throughout the Internet, including on marketplaces. Experts recommend: "Use an intelligent and reliable, fully automated software monitoring tool that supports you in monitoring the entire web - including portals, price comparison providers and shopping platforms.
3.) Consolidate the sales structure: building and maintaining a brand with trustworthy vendors is the only wise way in the long run. Identify by the best software monitoring that you can get for a reasonable price the unauthorized vendors. That enables your partners to generate revenues. This will help you to maintain the brand and its credibility.
Ultimately, a brand's commitment to enforcing pricing is a key factor in attracting and retaining high quality retailers as a premium brand. MAP only works if it is based and enforced on complete information. Online is here to stay. Knowledge and control of what happens online with the products will help to ensure that online and offline coexist and positively influence instead of cannibalizing each other.
Dynamic pricing is a system to always find the optimal price point, which is based on the fact that the prices change both on the basis of the own product costs and the prices of the competitors.
With the right dynamic pricing software based on the right and complete information, you can maximize profits and achieve other business goals.
An essential advantage of dynamic pricing is the possibility of exploiting potential profits. If the initial demand for a product is low and inventories need to be reduced, the price can be lowered to reduce inventories and generate revenue.
Similarly, if demand is high - for a seasonal product, for example - prices can be increased in line with demand.
These are simple facts that apply yesterday, today and tomorrow.
Knowledge of Competitors
Elsewhere we have sufficiently described how important it is to keep track of what competitors are doing. After all, our artificially intelligent software is based on it.
Implementing a dynamic pricing strategy requires knowledge of what competitors calculate and at the same time follow key industry and market trends.
The market research institute Forrester has proven that the use of price optimization software and the observation of competitors and trends can improve gross margins by up to 10%. Through the use of fully automatic dynamic pricing, profit increases of up to 25% could be achieved.
There is no reason why an e-commerce company should not think about implementing this strategy for the online store. In the long run, only those who have made the best decision in this respect will survive.
Dynamic pricing from the customer's perspective
There are hardly any disadvantages to dynamic pricing. Customers are used to paying different prices. The use of discounts and promotions often results in customers paying different prices for the same products. Take the famous example of petrol stations with different prices every few hours.
Nevertheless, the question of possible disadvantages arises? What can prevent the use of a dynamic pricing strategy from actually increasing sales and earnings?
It can lead to alienation of customers.
Nobody likes the feeling of having made a bad deal. Nobody likes the feeling of having paid more than others for the same product or service. eCommerce shops run the risk of alienating customers if they find out that someone has paid less for the same product.
This can lead to poor evaluations, complaints or reclaims.
That would be bad. The goal of every eCommerce shop is to establish and strengthen customer loyalty. It is simply much cheaper to retain an existing customer than to win a new one.
The best way to avoid customer losses due to supply behavior is to let customers know that prices are adjusted daily to keep pace with demand.
Every eCommerce shop operates in a highly competitive market. What they don't want is to leave customers to competitors.
And if it turns out that a shop is raising prices, customers are inclined to look around and see if they can find the same or a similar product cheaper elsewhere.
So in some cases the use of dynamic pricing can actually lead customers to competitors.
Therefore, you have to be able to rely on good technology. Incomplete information is as bad as incorrect information. Both lead to wrong decisions. Aimondo has placed the highest value on the basis from day one - information must be as complete as possible and must not allow any confusion with other products. There are information providers who hardly find more than 50% or even less of all offers of the same articles. And there are companies that only find what has a unique number.
That is not enough.
Due to the lack of a "second half" of competing offers, pricing is then wrong or at least not good enough to exploit the actual potential.
Dynamic pricing without the use of the most advanced and intelligent eCommerce pricing research and comparison technologies to optimize the own offerings based on the best data is dangerous.
A dynamic price strategy is best used when price optimization is automated. Not only because it would take far too much time and effort to do this manually, but also because people can misinterpret data and then draw the wrong conclusions.
Another additional advantage of using the best dynamic pricing technology is that it does not force a race to the bottom. With Aimondo clients can set the guidelines so that the lowest price is not lower than what can be afforded to sell quantity and still make a profit.
Although this article looks at both the advantages and disadvantages of a dynamic pricing strategy, there are definitely workarounds to each and every disadvantage.
At Aimondo we know that a dynamic pricing strategy is the key management decision for a healthy online business, but we believe it should be implemented in a very controlled manner. Only the best and complete data can be used as a basis for price optimization and only the most intelligent algorithms are suitable for designing offers and setting prices.
And because Aimondo hast he right devekopers, the sophisticated Artificial Intelligence (AI), the effficient Machine Learning (ML) algorithms plus the advantage of the extremely powerful and strong Cloud-based infrastructure it is the premium choice for successful eCommerce companies. And for manufacturers who want to know, whats going onin their industry. Alle components are language-ibndependant. That´s wha Aimondo can be used globally and actively seeks the global markets to become the industry leader.
The combination of being at the right time with the right product in the right markets and, with SaaS (Software as a Service), offering exactly the technology that the most advanced customers are looking for, makes Aimondo as interesting for the initiators as it is for shareholders.
When it comes to negotiating with manufacturers of branded goods, buyers are well advised to know the competition in the retail trade. Especially in the case of price-aggressive forms of distribution, one constantly experiences that branded goods are offered at prices that are below the normal purchase prices for normal dealers.
This may be because the competitor makes an offer to attract customers to his market or online shop. However, it is also possible that a special item was pushed into the market by the manufacturer via a special price. Or that the goods are offered cheaper in another country and found their way into the own country via grey channels.
All this should be known before you sit down at the negotiating table. It pays off. After all, the best achievable result is seldom achieved from the manufacturer as a buyer.
With intelligent software, almost all offers that are published online can be found without any gaps. Those on platforms, in online shops but also the offers of brick & mortar retailers when they are advertised via the net.
Aimondo´s Business Intelligence Module is a perfect tool in this respect. The system finds everything that can be found at any level of information depth via the flexible and particularly fast "Ad Hoc" search. Much more than a person normally learns in hours of research.
This important secondary function can lead in a single negotiation to a price bonus that covers the entire cost of Aimondo's complete services for a whole year.
Digitization and digital transformation are close to each other - but describe different situations. For example, if you wanted to digitize a company completely, you would either have to reproduce everything purely digitally or just use robots and intelligent devices with IoT. Everything would be digital.
Whether digitization or digital transformation, both terms are used differently. Because when it comes to companies and their strategies, then the terms are of considerable importance. It is worthwhile, therefore, to understand the grave differences between pure digitization and digital transformation.
Digitization is just the process of converting analog media into bits and bytes to be available digital. This can be documents, all files, movies, pictures and microfiches and much more. At the same time, analogue and physically existing products are always digitally imaged, copied or transmitted.
Digitization of content
Digitization can mean digitizing documents such as invoices, archives, products and using them for processing, storage or wider availability. For example, image and text recognition programs can be used to extract form content for use in processing systems. This is usually the first step in which businesses are getting closer to digitizing operations. Documents and analog content are converted to digital form.
Automation and digitization
Digitization is often used in connection with the automation of production or processes. Already existing processes are digitally reproduced in order to save working by automating them. For example: An order is issued and prepared as a process. The shipping label is created, an invoice is generated, booked and sent, the warehouse is informed and the shipping including all documents prepared. In this way, the entire process is transformed into a fully automated digital workflow.
A Digital Business is setting up business areas, business models and even entire companies purely digitally. New technology elements and new digital possibilities are changing entire areas and even companies in a whole. Consistent and constant use of new techniques are the tactical method to implement this strategy. Processes such as constant supply chain optimization, logistics and customer loyalty are essential elements. With business partners, we aim to achieve maximum networking and data exchange.
When it comes to digital transformation, you can see the business units and their processes too. However, the understanding goes much further into the holistic planning of the future. It goes beyond the scope of simple adjustments and use of new digital tools. In the digital transformation solutions are found or tasks redefined, which are solved with the help of technology. Thus, the paper and results of human labor are not simply digitized and then processed, but e.g. considering whether the process is still needed or whether it can not be simplified with the help of a new technology or completely automated.
Digital transformation also means the execution of tasks with the best possible technical means. This draws on topics such as "Agile", "Design Thinking", "Brainstorming" and other current ways of working needed to differentiate tasks. Once you have understood a topic thoroughly, you can also solve it with technical means and use new technologies.
Important here is the understanding that digital transformation is never triggered by technology. It is always about solving a task or a problem or basically finding a new approach. The task-centered solution is always the start of the digital transformation. Not the technology as such.
Digitization leads to "Digital Business". The "Digital Transformation" is based on "Digital Business" and "Digitalization"
Google says: "Digital transformation is the profound and accelerating transformation of business activities, processes, competencies and models to fully leverage the changes and opportunities of digital technologies and their impact across society in a strategic and prioritized way."
Digitization has led to digital content. This content can be processed in digitized processes. The availability and applicability of new technologies leads to the development of a digital business strategy. Digital transformation goes one step further. Of course you need digital content, digital processes and a digital business model. Digital transformation captures all aspects of the business. Customer needs as well as innovative new products. These opportunities and challenges form the basis of a new economy with new priorities and new rules. Digital transformation is a question of survival for businesses. One that does not necessarily begin with a disruption, as the destruction of previous methods. Rather, it is about solving changing tasks and new problems in destroyed traditional market structures. The transformation is for existing companies the smoothest possible transition to the use of best technologies in order to derive "best practice" solutions for all tasks. New companies find it easier to position themselves in damaged or destroyed market structures. They can try and test wrong, non-functioning ways without much damage. Newcomers who assert themselves are growing at a record pace to size regions of unprecedented dimensions. Even as a purely digital service provider or dealer without significant physical presence.
The relationship becomes clear when considering the elements of a successful digital transformation. Many companies only see the first steps of digitalization and only try to replicate existing processes, business areas and markets with digital tools and processes. The problem here is that the new opportunities and challenges as well as the new opportunities are ignored.
Digital transformation needs digitization, but: it is just a module. One should not get bogged down in digitization and lose sight of the goal of digital transformation.
Aimondo is a purely digital company that enables the digital transformation of online marketers and is privileged to have been a "transformed company" from day one.
No, they free from routine work. The decisions are made in the end by people. The manpower that
was previously used for research and extensive pricing can be used to implement increased sales.
The complex AI-based decisions that Aimondo proposes or makes are based on intensive research
carried out by self-learning algorithms. They help to make better decisions by giving us people a
better overview of the decision-making situation.
We distinguish between two modes in which we make decisions. Namely "fast thinking" and "slow
thinking". With fast thinking, we draw quick conclusions from a few facts. With these we make on
rather uninformed basis a predominant intuitive decision. Here the human being is the biggest
source of errors within this "structured routines".
Aimondo's artificial intelligence helps to get out of this „fast thinking“, which is usually faulty, and to weigh more facts, information and influencing factors against each other in the mode of slow
thinking. In Aimondo Dynamic Pricing, these considerations are incorporated into decisions that
affect entire article groups and assortments if they follow a comparable logic.
In practice, customers report that they not only achieve over 20% more sales but also increase their adjusted profit by a double-digit percentage. The relatively low costs of deployment thus contribute to the fact that working conditions are improved, incomes increased or new business fields openedup through the release of funds.
What is certain is that the use of digitalized business intelligence and algorithm-based pricing will
change the division of labor between man and machine. In eCommerce as well as transferred
analogously to other areas. The Aimondo Group is well on the way to becoming one of the strongest innovation drivers of this global change.