renner_penner

Magic Quadrant - Renner Penner

incuda Best Practice Sharing

How to push the boundaries in Category Management with user interest data.

incuda Background:

incuda provides a Business Intelligence (BI) platform and expertise for retailers and supports them in going from data insights to full governance of strategy, tactics and operations. We enable fast change from a traditional retail business to data-driven business. We help our clients to stay focused on business by handling:
      • End-to-end Business Intelligence transition
      • Data integration
      • Business Intelligence operations

Our customers can benefit from our retail focused platform as well as market ready, proven, and agile solutions which can be adapted to their business needs in no time. The flexibility and openness of the platform enables further extensions and customizations on demand.
At incuda we believe that data not only helps to drive change, but also supports in making better decisions every day.

The Problem: Customer Expectations are changing faster than traditional planning

Shoppers are increasingly looking for instant gratification. They want products faster and with a personalized shopping experience. Their expectations are forcing retailers to rethink strategies and tune up execution.

Due to the growing use of the internet, all offers have become more transparent and, at the same time, demand and preferences from consumers have become more volatile.

Today’s consumers have more information at their fingertips than ever before. The ability to compare services and prices online and easily order from different providers, even across long distances, decreases the loyalty and the stability of a company’s customer base. At the same time, it has also gotten easier than before to attract new customers with the right offer.

In this volatile environment, managing and optimizing category structure and inventory depends more and more on understanding the expectation of consumers, the changing market trends, and the total sales potential. Purchasing and inventory planning which cannot respond to these trends fast enough will face a higher risk, such as that of selling out on the attractive products and being left behind with overstock for less attractive products.

Solution: incuda’s approach – how incuda helps to respond faster to the market

We help Category Managers with an enhanced version of the “Renner Penner” (Magic Quadrant) analysis.

The traditional analysis is based on orders and revenues, and groups the products into four quadrants according to the sales and order count. Because this approach is focused on order data, the Category managers have no information about all the visitors who do not buy.

Similar analyses could be available from Web-analytics tools. You can find out the visitor’s navigation and view events in these tools, but these do not have information on cancellation, returns, or profit metrics.

The incuda “Renner Penner” analysis adds information about customer “interest” to the order data, especially if visitors look at products or put them in the shopping basket. The order event is a crucial step but following this we track cancellations and returns and can report on profit metrics. Information on stock level and data aggregation on brand or category level are a few additional features of the analysis.

The following chart shows:

     • X axis: Raw data of product interest (number of product view events.)
     • Y axis: The conversion probability (number of orders by number of view events.)
     • Size of the bubble: total revenue generated by the products.

The raw data in the “Renner Penner” analysis:

       
The raw data shows strong clusters of products and big empty spaces.

To improve the usability of the analysis, we normalize the data by normalizing outliers and grouping the products into four quadrants.

The Matrix is divided into four quadrants based on an analysis of View Events and Order Conversion, as shown in the diagram below:

The normalized “Renner Penner” chart:

Short description and ideas for the interpretation of our quadrants:

▪ Renner:

They generate high interest (many view events) and show a high order conversion. These are the products which are very attractive, and you sell a lot, they generate a high amount of total revenue (maybe you call them your “A” products).
Recommendation: Check which of these products have a high/low profit margin. If you own the brand or have a special agreement with the manufacturer you might have high margins. If it is a highly attractive product from an established brand and available from many retailers (“commodity”), margin might be slim.

▪ Hype:

These products are viewed often by your visitors. They are considered “interesting”, but for some reason, people don’t buy it.
Recommendation: In the traditional “Renner Penner” analysis these products would be considered unattractive as they generate low sales numbers and at the same time, they often have higher prices, so even putting the products on stock is expensive.

The low conversion rate might depend on the following reasons:
▪ If the price is unattractive compared to the competitors or delivery time too long, you might try to improve here.
▪ If the price level is high (luxury product), then use the product for traffic acquisition and branding: you can plan with lock stock levels. But showing these products to the market brings you visitors at lower cost and gives you a high-value perception as a retailer. You should navigate these visitors from the hype-pages to other, more affordable products, where they are able or willing to buy.

▪ Penner:

Visitors are rarely interested in these products, and even if they look at the products the probability of purchase is low. With the traditional “Renner Penner” you might consider removing these products from your offering. With the incuda approach you can follow a long-tail approach.
Recommendation: incuda “Renner Penner” provides you the link from the order and view events to the visitors. This allows you to segment users and products (with higher margins) and use a personalized approach to show a relevant selection out of a wide range of products to many single visitors. With the higher relevance per user and the increased conversion, you create new sales opportunities, probably in a lower-competitive market segment (few retailers can handle long-tail strategies).

▪ Hidden Champions:

Few people look at these products, but many of them are buying the product. The general approach is to grow these products into the “Renner” quadrant.
Recommendation: Check which part of these hidden champions are products which are “demand-driven”, e.g. food or consumable products. You might offer special services or implement push campaigns to remind customers and create repeat purchases.
To identify potential “Winners”, link the data to “early mover” visitors and customers who buy upcoming top products early on and get a short-list of products which should be pro-actively marketed to a wider audience.

Benefits for Category Managers:

The analysis addresses several challenges for category and offer management in a dynamic environment. Additionally, it supports the joint efforts from channel managers, marketers and category managers by linking product interest with channel interaction and the customer view. Further benefits are mentioned below.

More dynamic assortment planning and optimization through continuous monitoring of purchasing behavior of targeted groups. incuda BI enables the managers with detailed data on product performance with what items the visitors are viewed in the web shop, items added in order baskets or added and removed, ordered, sold and returned. incuda BI further provides this analysis in conjunction with online marketing data to know which campaigns yields best and with the best-selling products. With this analysis shop managers can drill down to gain more insights on how they can optimize their categories for better product assortment, and effective campaigns. With detail insights from the product performance, inventory turnover can be increased as a result of better assortment optimization and space productivity.

Number of prospects * potential rates are vital because they reveal the potentials for more sales, and stronger customer loyalty. With incuda BI, category managers learn more about actual conversion rates as the analysis establishes a good relationship with advertising, marketing efforts, sales, and return ratios to provide more insights. Formalizing the pricing strategy is important for the category managers, because with detail insights from the Renner Penner they identify which products to raise and lower prices.
Connecting categories with channels and customers gives Marketing, CRM and shopping managers a common language to work together. Using traffic and user data, the Renner Penner helps establish a solid connection which is the key in driving up sales.

Conclusion:

For retail companies to maintain a competitive edge in an accelerating marketplace, it is becoming increasingly important for them to seek proactive methods of connecting categories with channels and customers in innovative way. With the help and expertise of incuda BI, retailers stand to be able to achieve deeper understanding of their customer data. To achieve this “Renner Penner” allows Category Managers to have a better understanding of ongoing buying cycles, the overall potential in the market and changes in market trends.

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