In my recent posts I have shown which insights you can gain with the help of price elasticity and how this helps you to better understand your entire product range and to price it accordingly. The splitting of your product portfolio into article roles, such as common and focus articles as well as basic and skimming items, was particularly significant. It provides a valid basis for a holistic, AI-supported pricing strategy by answering the following questions:

• Which product segments can best serve which of your target KPIs?
• Which product groups are particularly important for your customers and therefore particularly effective in marketing campaigns?
• Which degree of automation should be chosen when using a dynamic pricing software?

We will now answer all these questions step by step. Let’s start with the basic and skimming articles. These article groups are usually not very price-sensitive and therefore less competitive relevant. This is mainly due to the fact that consumers have only a low price awareness for these products – either because they rarely buy these articles and/or because they do not have a high investment value associated with them. (You may recall the examples: pots and spices.) Basic and skimming items can therefore be pretty useful to increase your target KPI Gross Profit. For these article groups, my recommendation is: The pricing shall be done fully automated by an AI-supported dynamic pricing software to effectively capture the existing gross profit potential. Especially because basic and skimming products are not in the focus of your customers, it makes little sense to invest a lot of work in these articles. Especially since manual pricing is also hardly to be done in a meaningful way anymore, since on the one hand too many influencing factors have to be taken into account (such as daily stock, daily demand, weather, holidays, seasonal characteristics etc.) and on the other hand the sheer quantity of such articles is too large. Basic and skimming items make up about 60-80% of a total assortment – in principle, the broader and deeper the assortment, the higher the proportion. Therefore, automating the price calculation and price setting for these assortment parts is particularly effective.

Different rules apply to common and focus articles. These articles are highly price-sensitive and therefore enormously relevant for your competition. Your customers are highly likely to notice price changes for these articles and they will react to them. The good news is: You can use this to your advantage! By increasingly integrating common and focus products into your marketing campaigns and by setting prices in a way that is factually valid and strategically well-founded. In this way, you can control the KPIs turnover, sales, frequency and market share in a very targeted manner. If you offer these articles at special prices, you can attract your customers to your store in a plannable way. In this way, you can generate corresponding turnover and sales – and at the same time increase the frequency of your store. In the medium and long term, you will secure your position in the market and gain additional market share.

What is important is the strategic interaction of the two article groups when setting prices. If you have the basic and skimming articles priced by an AI, up to 80% of your assortment will be priced fully automatically. This saves you a lot of time for manual price maintenance and also allows you to make the most of your gross profit potential. Conversely, this means that your Category and Pricing Management has gained time which it can use for planning the strategic use of the common and focus articles (e.g. in promotions or marketing campaigns). It also means that you can use a portion of the additional gross profit you generated to price those products very attractively, that are in the price focus of your customers. Here, an AI pricing software will support you and provide you with appropriate price suggestions that take into account all important general conditions. In addition, a truly powerful dynamic pricing solution automatically provides a forecast of KPI effects. This gives your category and pricing managers a differentiated basis for each pricing decision and allows them to set prices manually. For me, this form of man-machine cooperation is particularly remarkable, because here the algorithm with complex mathematics and statistics complements the competence and proven gut feeling of the assortment professionals.

Are you now asking yourself what you need to use an AI solution for price optimization? Then look forward to my next post! Or just ask me directly!

Mrs Pricing

In my last blog post I introduced the mathematical concept of price elasticity and the benefits it brings to AI-driven price optimization. As promised, in my post today I explain how you can use price elasticity to create a strategic basis for the use of an AI pricing solution.

With the help of price elasticity you can determine exactly how price sensitive and competitive your products are – ergo: which roles your individual articles play within your overall assortment and what this should mean for the pricing of these articles. In principle, the following differentiation has proven to be useful:

• Common and Focus Articles and
• Basic and Skimming Items.

Customers generally have only a few product prices in mind when shopping. Typically, they remember the prices of the products they buy often and, above all, regularly. In a supermarket, for example, these are basic foods such as bread, butter or eggs. Based on these items, consumers judge whether a retailer is expensive or not because they have corresponding comparison prices in their minds. Consumers therefore react very strongly (both positively and negatively) to price changes for these items, which makes them highly relevant to competition for you as a retailer: We are talking here about common and focus articles. Products that take on such a role are crucial for your image. They enable you to proactively shape your price image and then sustainably underpin it. In the course of AI-controlled price optimization, you will therefore pay particular attention to these articles and apply a dedicated strategy for the specific requirements of these assortment components in order to

• actively increase your customer and purchase frequency,
• to strengthen and expand your brand in competition and
• optimize target KPIs such as turnover and sales.

Basic and skimming items, on the other hand, will serve a different purpose for you and will primarily serve KPIs such as gross profit and margin. Basic and skimming items are hardly or not at all in the focus of your consumers and are therefore hardly price sensitive and just as little relevant to competition. Why is this so? Skimming articles are often longtail products. In our supermarket example, these would be pots or irons. Customers buy these items very rarely, sothey have hardly any comparison prices in mind. The situation is similar with basic articles. These are also rarely bought, but regularly – spices are a good example here. Because consumers are less price-conscious, all these articles are very well suited for optimizing gross profit and margins. It is particularly noteworthy that on average up to 80% of a product range consists of basic and skimming items – so the leverage for your optimisation potential is enormous!

Now the question remains how to use the knowledge gained to control your price optimization by means of an AI. You already suspect it, don’t you? Exactly! That’s what my next article is about. For all those who are rather impatient like me, I will of course provide a shortcut ;-)

Mrs Pricing

In my blog post today, I would like to present THE all-rounder for dynamic price optimization: The Price elasticity. Mathematically as well as strategically, it is capable of great things! I am convinced that there is no other approach that works as efficiently, economically and above all sustainably as the price elasticity.What is particularly remarkable is that it not only provides an ideal basis for price differentiation, but can also decisively support your entire pricing process chain, including:

• The strategic planning of your pricing policy,- the determination of your most competition-relevant assortment components,
• the detection of the products that are particularly important for your customers and thus for your price image,
• the simulation of the earning potentials of various strategic approaches to pricing,
• up to the AI-controlled calculation of market-driven, demand-oriented prices for your entire product range.

Let’s first have a look at how price elasticity is determined and what it means in concrete terms: Price elasticity is determined via the relationship between price and sales. At the individual product level, price-sales functions are thus formed, which represent in the form of a mathematical curve at which price a product was sold and how often. From such a price-sales function, it can now be derived how the demand for a product changes when the price is changed. Strictly speaking, we are therefore actually talking about the elasticity of demand rather than that of the price. Depending on how elastic the demand for a product is, this provides information about:

• How sensitive your customers are to a price change,
• how relevant this product is in your competitive environment and
• how you should treat this product within your pricing strategy.

How do you now use this information for price optimization? If the demand for a product is highly elastic, the sales of this product will change significantly if you change the price (positive or negative). This means that your customers will reactvery sensitively to a price change for such a product. At the same time, in most cases this will mean that this product is also highly relevant for your competitive environment. For this reason, price optimization should be carried out with particular attention for products that are very price-elastic. The situation is different for products whose demand is not very elastic. Here, price changes havea comparatively small effect on the sales. This means that your customers
tolerate price changes very well or do not even notice them at all. This also means that the competitive relevance of such products is significantly lower. In terms of price optimization, this means that you should use these products to operate effectively and sustainably.

What is the next step?

As a first step, you should use price elasticity to analyze your assortment and derive the various functions of your articles. From this you will draw very important, strategic conclusions that will form the basis for AI-controlled price optimization. But more about this in my next post!

You don’t have that much patience? Then reach out to us for a demo.

Mrs Pricing

You know what my first point of contact with AI was? It was in 1991, when I was 7 years old and completely enthusiastic about K.I.T.T. – not (only) about the car, butespecially about the concept of an “intelligent” companion, who is always there, helping and supporting where mankind reaches its limits. Today, almost 30 years later, I work with a (real) AI system every day – and my enthusiasm from back then is greater than ever! Why AI technologies are so inspiring, I will outline in this blog post. And if you’re thinking now “This is way too technical for me.” – staywith it anyway! Because it is above all economically profitable!

Clearly defining the construct of artificial intelligence is incredibly difficult. If only because the term intelligence alone can hardly be clearly defined. That’s why AI is currently used almost inflationarily as a buzzword – in principle (almost) always when it comes to machine learning. However, there are some very decisive technological nuances that make the difference, especially in economic terms.

Machine Learning is the generic term for various processes that can be used within an artificial system. Machine learning in itself means “only” that an artificial system is capable of analysing data and uncovering patterns or regularities within the data. Based on this, the system can also evaluate unknowndata. So far, so good. But this kind of machine learning is, in my opinion, far from being an AI. For me, artificial intelligence starts where an artificial system is able to adapt to changes in its environment and to develop itself accordingly. This is where reinforcement learning comes into play.

Reinforcement Learning – a subdomain of machine learning – is a very powerful algorithmic procedure and describes the concept of self-enhancing learning. This means that this type of learning is always linked to a very concrete goal, which is approached step by step. Every single learning step is checked and evaluated: If it serves to achieve the goal, it is rewarded. If it does not, it is punished. Do you already see where this leads? A system that develops itself in this way learns to “think” economically. In doing so, it continuously adapts to the given environmental conditions in such a way that it achieves the specified goal. By theway: If you are now wondering whether an AI is more likely to reward itself with an ice cream or rather with chocolate, just ask me. ;-)

What does this have to do with Dynamic Pricing? Especially in dynamic price optimization, I think it is very important to rely on an AI that develops itself further through reinforcement learning. Because for you, this means that you actively control the algorithm from the outset. You specify the economic goal (such as sales, turnover, profit or margin) and the procedure then learns a strategy for your individual business with which the KPIs you have specified are best achieved. Because your target is also the reward value for the AI, the process will constantly evolve to ensure that your target KPIs are met at all times – even when environmental conditions change (inventory, demand, competition, etc.).

So if you have not yet worked with AI, because these approaches seemed like a black box that you cannot master, the complete opposite is the case. You set the global strategy and the concrete goals – the AI just does all the work for which your time is too precious (and/or has long since ceased to be enough)!

You wonder how this works in daily practice? We can look at it together immediately!

Mrs Pricing

One of more common, traditional approaches to establishing price differentiation comes in the form of rule-based systems, or rule engines. They implement predefined pricing rules in a prescribed pattern. These systems often set item prices exclusively based on competitor prices, which the system’s rules are set to exceed or undercut by a certain percentage. This works just as statically as it sounds, but it works reliably.

The thing is, retailers using rule engines end up with two glaring blind spots in their pricing models:

1. They never find out if they can step out of the shadow of their competitors.
2. They give away considerable profit potential, turnover, gross profit and, ultimately, market share.

This is because rule-based systems don’t offer the ability to intelligently adapt to changes in the business environment. With rule-based solutions, you will only ever take a reactive role in competition, as you’re unable to actively shape prices yourself. Thus, this process often results in price-up or price-down spirals, because retailers basically only underbid or outbid each other. A consistent price development, which the customer can also understand, is therefore not feasible.

The increasing scale of product ranges and the increasing speed of the market also pose new challenges for pricing, requiring you to be increasingly dynamic in order to maintain competitiveness and reinforce your own long-term position in the market. The solution comes in the form of intelligent algorithms that price your entire product range within seconds, as they automatically take into account all general conditions and achieve the KPIs you can specify with pinpoint accuracy.

How does this work? How can an algorithm know what your goals are and, more importantly, how does it know what it has to do to achieve them?

It all comes down to realizing the promise of “reinforcement learning” – not only one of the most powerful AI procedures, but also the most common form of learning for humans and other highly developed species. Any artificial system becomes a real AI only when its programmed intelligence can be further developed independent of human intervention through reinforcement learning. What impact can this have on your business? Reach out to connect with our experts.

Mrs Pricing

Dynamic Pricing is the proven “corner store” principle – rethought for the digital age.

Small corner stores always used a somewhat volatile pricing policy based on experience and gut feeling. For example, close to closing, they generally offered bread or fresh products at a discount in order for the retailer to sell out. But at least three things have changed massively since then:

1. he scale of assortments in combination with the complexity of influencing factors that have to be taken into account for the pricing process.
2. The level of price transparency has risen enormously, as customers are now able to compare every product price, at any time, online.
3. The speed of market and demand changes has never been as fast as it is now.

Dynamic Pricing enables you as a retailer to react to these massive changes quickly and effectively. Through algorithmically optimized pricing, you are able to establish market-driven prices based on supply and demand, guarantee sustainable price changes and avoid disastrous price spirals and price distortions.

Dynamic Pricing – aka dynamic price optimization – means that you can regularly adjust product prices to correspond to the current market and current demand. AI-driven software observes all contextual conditions that are relevant for the market environment and for a retailer’s entire product range. It allows you to include factors such as demand for each of item, your current stock levels and competitor approach into consideration.

Then, based on the findings and established business goals and pricing parameters, such as margin, sales, market control and more, the AI software delivers optimized price recommendations, and executes price changes, automatically or semi-automatically. If you would like to see Dynamic Pricing in action, reach out to us for a demo.

Mrs Pricing

Given the current situation with the COVID-19 outbreak, it’s important to us that you know we have taken numerous measures to ensure your health, the health of our employees and the smooth operation of our customers' stores.

We are diligently following the recommendations of global government and health authorities in order to guarantee that there is as little disruption to your business as possible. We are committed to ensuring the regular operation and support for the systems we supply, and to protecting the important infrastructure you operate. Even in this unique situation, we will continue to deliver the quality service and commitment you are used to.

To minimize the risk of infection, our employees are working from home if at all possible. In those areas where this is not possible, we are taking all the necessary precautions to maintain their health and safety, as well as the continuity of our operations. Please understand that we will no longer be able to hold on-site meetings at your premises until further notice and that we will therefore use video conferences for meetings whenever possible. We ask for your understanding in this.

If you have any questions or need support, please connect with your primary GK contacts, and we will answer you as soon as possible. We are convinced that we will get through this together with you.

GK Software, the international market leader for store solutions, today announced the completion of Custom Data Processing Inc.’s (CDP) certification for online eWIC payments. This will help retailers, including Smart & Final, provide faster, more convenient and secure online eWIC payment processes.

After Oct. 1, 2020, The Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) will require retailers to provide electronic access to benefits. Called eWIC, the program served nearly seven million participants per month in 2018. The electronic mandate is designed to modernize and remove friction from the checkout process and eliminate paper certificates. As the program transitions to electronic payments, vendors are able to simplify the process, driving efficiency for both retailers and users.  

The eWIC certification recognizes that GK Software’s Integrated ECR System is capable of managing payments through one unified processor, making transactions at the point of sale faster and easier to operate. With online eWIC, the transaction is completed in real time through the POS terminal and WIC Authority network processor. 

“As retailers look to update their payments to comply with eWIC regulations, this is the perfect time to evaluate their current features to ensure their infrastructure is future-proof across the enterprise,” said Michael Jaszczyk, CEO, GK Software USA. “This is the latest example of the need for retailers to regularly evaluate how they can improve the customer experience and drive loyalty through technology and use platforms that deliver high levels of business agility and scalability.” 

GK Software’s online eWIC certification with CDP includes the following states: AK, AZ, CA, CO, DE, FL, HI, IA, ID, KS, KY, MA, MN, NE, NV, OR, SD, WA, WI, WV.

GK Software SE is reinforcing its claim to be the world’s leading provider of software solutions for the retail sector with its cloud4retail platform. cloud4retail combines what is absolutely essential for a forward-looking solution in one platform: various cloud options, ranging from private to hybrid and even multi-tenant, offer flexibility and the highest levels of performance for innovative retailers.

GK Software will be demonstrating this enormous flexibility and the expansion opportunities, which the world’s leading cloud platform, cloud4retail, offers in conjunction with artificial intelligence, at the EuroShop retail trade fair on booth G42 in hall 6. cloud4retail brings together the leading solutions for large retailers with international operations through its OmniPOS, Mobile Consumer Assistant and AIR (Artificial Intelligence for Retail) components. cloud4retail provides essential services like a shopping basket, price calculations or loyalty & promotions, within its open platform. It is possible to supplement the overall solution with additional functions directly from the OmniPOS standard software or as micro-services, which are simple and quick to implement and can come from a variety of different sources. The open platform enables retailers to test new concepts very quickly by using various enhancement opportunities – ranging from APIs to HTML-based app enablement – without having to change the software core in the process. This means that innovative solutions for item detection with the help of cameras or even intelligent shelves can be integrated quickly and tested in practice, for example. The classic cashier-operated checkout plays less and less of a role in these scenarios, but all the checkout functions still have to be made available as a top-quality service. Whether you need a frictionless store, self-scanning with smartphones or mobile applications on each possible device – the cloud4retail platform integrates all the touch points in an all-embracing, end-to-end IT concept.

GK is inviting programmers to a hackathon at the EuroShop fair to demonstrate its product; this will enable users to test how easy it is to develop new functions on the basis of the cloud4retail platform. One example of how to quickly introduce new concepts will be a fashion pop-up store on the GK booth; this will demonstrate how innovative concepts can be quickly handled by open services architecture in order to inspire customers as well as seamlessly network all the channels and formats.

The issue of cloud services is one of the most important items on the agenda for the retail sector. cloud4retail has already been fully designed for use in a cloud and SAP is already selling it. GK Software will be presenting the new cloud services at the EuroShop fair; as a result of them, it is even possible for very large, international organisations to use the OmniPOS leading enterprise solution in a cloud. All the options, ranging from private to hybrid and even a multi-tenant cloud, are feasible here in order to satisfy what retailers of different sizes require.

Another major issue at the EuroShop fair will be the topic of artificial intelligence. The major focus will be on consistent, individualised services for all the channels as well as automated, dynamic pricing on the basis of machine learning. Artificial intelligence forms an integral part of cloud4retail on the basis of AIR platform (the Artificial Intelligence for Retail). AIR makes available the tools and additional means for specific solutions to meet precise retail requirements like dynamic pricing or personalisation.

GK Software SE will also be presenting the latest version of its mobile merchandise management solution at the EuroShop fair. It provides all the merchandise management processes in a store directly out of a cloud on an extremely modern technological basis; this is available as an end-to-end service, online and offline, on different mobile devices and with a direct link to the central systems.

Another major topic this year will be the issue of fiscalisation. Deutsche Fiskal, a subsidiary of GK Software, will be presenting its Fiskal Cloud solution on the GK booth; it enables retailers to meet the challenges of the German “Kassensicherungsverordnung” (Cash Register Security rules) by using a low-cost and future-proof cloud solution. 

GK Software today announced a technology partnership with Kronos Incorporated to embed the next-generation Workforce Dimensions suite into GK’s OmniPOS platform. This partnership enables frontline retail employees to access the revolutionary workforce management solution from Kronos at every point of sale terminal and all GK OmniPOS touchpoints. This intuitive, frictionless interface establishes a more flexible and productive workplace environment that empowers employees and promotes more efficient and profitable store operations at organizations that deploy both solutions.

GK Software's cloud-enabled, agile OmniPOS platform has been identified as the most robust POS platform by Forrester and is one of the fastest-growing POS platforms worldwide. Workforce Dimensions is the first intelligent workforce management solution. The cloud-native suite leverages artificial intelligence to provide unprecedented real-time insights, recommendations, and analytics.

“By partnering with the established leader in workforce management applications for hourly employees, we are creating a unique opportunity for retailers to leverage a single, centralized platform to manage the full scope of their store operations,” said Michael Jaszczyk, CEO, GK Software USA. “Our focus on eliminating the friction associated with the checkout process perfectly aligns with the Kronos ethos of doing the same for workforce empowerment. Together, we can offer the most robust, simplified experience for store managers, associates and customers – a requirement for success in modern retail.”

The integration of Workforce Dimensions into GK’s robust, cloud-enabled OmniPOS platform will allow employees to significantly reduce the time and complexity associated with managing administrative workforce processes. Now, they will have the ability to clock in and out, view their schedules, request and accept shift changes, manage time off and more, right at the point of sale. This increased flexibility will improve store efficiency, reduce administrative work, support real-time data-driven workforce optimization and improve the employee experience.

“Our technology partnership with GK is yet another example of the new era of efficiency for modern store operations,” said Michael May, senior director, Workforce Dimensions Technology Partner Network, Kronos. “We designed Workforce Dimensions from the ground up to easily integrate with and embed inside of workplace applications where employees already spend most of their day. This creates a more engaging workplace experience while allowing them to remain focused on customer service and driving the business forward.”