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It’s no secret: in the retail industry, price is a key factor for differentiation and competitiveness. Thus, retailers and pure players pay particular attention to the design of their pricing strategies. To deploy a coherent strategy in relation to the market and position themselves effectively, it is now imperative to base their approach on up-to-date data, both from their own sales point and from competitor stores – including practiced prices, promotions, available products, deployed ranges, etc. Regardless of their origin, these data form the foundation of a competitive pricing strategy. How then can their collection be optimized to use only the most relevant data possible? How can one have the most current offline data to align with the web’s reactivity?

To address this issue, Optimix has developed two ergonomic, fully customizable, and results-oriented solutions: the Web Data Collect module – a tool for capturing data from competitor websites – and the Scan In Store module.

In this article, we focus on data collection in points of sale, via the Scan In Store module.

Scan In Store: optimizing data collection in price surveying at the point of sale

Scan In Store: optimizing data collection in price surveying at the point of sale

While external service providers offer in-store data collection services, these operations often have limited interest for products with high competitive potential and/or whose prices fluctuate very frequently. Indeed, the delay in transmitting the results of a collection campaign carried out by an external provider is a hindrance to the rapid integration of sensitive data into your pricing strategy. Yet, to remain competitive against competitors’ prices that are regularly changed, it is necessary to be reactive and flexible: otherwise, it’s impossible to establish a pricing strategy in accordance with the latest market updates. The emergence of digital and pure players has reinforced this requirement, dictating a new level of reactivity to the market: real-time.

Who knows if your competitor has not changed the price of a product with high competitive potential two days, a day, or three hours after the last collection you have? Therefore, are your pricing operations still relevant?

Scan In Store offers a tailored response to these issues to best manage data collection: reactivity, recurrence, and reliability are its watchwords. Do you wish your users to check the prices of the current flagship product at your competitors every morning? No problem, all it takes is a smartphone.

Scan In Store: organizing targeted and regular data collections

An Accessible and Ergonomic Application

Scan In Store is a mobile application dedicated to in-store price surveys. Once installed on a smartphone, it enables store teams to record product data present in sales points: labels, prices, barcodes, and photographs.

Initially, headquarters defines the scope of the data collection: the target store(s), the date of the survey, the person in charge, and the products involved. The user tasked with conducting the survey receives a mission order in their application summarizing all this information. They then visit the sales point to photograph labels and products with their smartphone and directly upload them into Scan In Store.

Once this step is completed, the software takes over. Scan In Store’s artificial intelligence extracts key elements from the photographed labels: the product label, its shelf price, and its barcode. It adds these elements to the existing database and presents them to the operator in the form of analysis tables to facilitate reading and understanding. The user consults these data via the Scan In Store interface, deployed on smartphones, tablets, and computers.

An Application Suited for Product Matching and Price Comparison

Aware of the stakes involved in data collection – product matching, pricing strategy, range coherence, etc. –, Optimix has developed an application suited to the diversity of needs justifying a data collection. For this purpose, three data collection operations are configurable.

Price Scan on Match: in-store price survey of already matched products at competitors

Let’s delve right into the heart of the matter. The Price Scan on Match operation updates in real-time the targeted product prices according to your needs and competitive scope. It meets a strategic necessity: having an up-to-date price survey to adopt a relevant price positioning.

Let’s illustrate its functioning with a concrete example: the store of the brand wishes to perfect the price positioning of products sold in the appetizer aisle. To do this, headquarters defines in Scan In Store a list of brand products, national brand, or private label: chips, olives, pretzels, etc. The chaining of these products is already done; all that’s left is to update the competitors’ prices.

Armed with their smartphone, the user then visits the competitor’s store and proceeds with the data collection, according to the pre-established list. For each product, the application automatically detects the existing matching and updates the competitor’s product price in real time. The periodically collected data is directly integrated into Scan In Store’s analysis tables, and possibly into the Optimix Pricing Analytics application suite, detailed here. Thanks to this interconnection of Optimix modules, you have the ability to collect and integrate your competitors’ prices into your pricing strategy in real time.

The only prerequisite for this method is that the matching between your products and those of the competition must already be established. This operation of chaining is strategic, as it is impossible to compare brand products and competitors’ products without it. The Scan In Store module ensures, by involving two types of operations dedicated to chaining described below, that your matching is effective, reliable, and meets your needs.

Collect, Scan and Match: data matching on a closed list of products

This operation configuration consists of collecting data to perform product matching directly in the competitor’s point of sale. It relies on the intervention of a user who visits the competitor’s store, checks the available products, establishes links between products, and carries out the chaining on the spot.

Let’s revisit our example.

To enhance the competitiveness of its snack aisle, the retailer wishes to collect data from a competing store, including available products – identical or comparable to the retailer’s, prices, descriptions, and barcodes. For this purpose, the headquarters selects in Scan In Store the retailer’s products for which the linkage is not yet available. If these products are not yet listed in the application, a prior data collection in the retailer’s store is necessary to update the database. Afterward, the user visits the competing store. Their goal is to match the competitor’s snack aisle products with those of the retailer.

To optimize and ensure the reliability of this process, they have access, through the application, to photographs of the retailer’s products, along with their descriptions, barcodes, and prices. When a match is established between two products, the user photographs the competitor’s product and its label. By doing so, they validate the match directly in the aisle and import the competitor’s data – prices, barcodes, description, photographs – into Scan In Store.

Walk, Scan, and Match: Data collection and on-the-fly linkage

This last type of operation also aims to establish product matches. However, the data collection method differs. The user does not have predefined target products to scan. During their visit to the competitor’s point of sale, they will gather references on the fly, without a specific focus on particular products.

The matching operation will only take place afterward, following the in-store collection. Once the collected data are imported into the application, an operator establishes and validates the product correspondences from the interface. This type of collection has the advantage of reducing the time spent in the competitor’s store and of complementing your database as your team’s availability allows.

In these two matching operations, product photographs serve as a safeguard. Indeed, they allow for the verification of collected data and the established matches, ensuring that the database is 100% reliable and usable. To further optimize its function and better meet the on-the-ground needs of the retail industry, Optimix has equipped Scan In Store with powerful artificial intelligence, complemented by human intelligence.

Optimizing your performance through Artificial Intelligence and machine learning

Scan In Store’s artificial intelligence operates at several levels. It is found, for example, in the reading and extraction of label data, as well as in the automatic matching of products. To ensure the application’s efficiency, this artificial intelligence operates on the principle of Machine Learning.

To understand what this means, let’s consider an example: the software makes a data interpretation error from a label, indicating a price of €0.59 instead of €5.90. However, as we have seen, operators can correct incorrect information from the Scan In Store interface. They simply need to look at the photographs of the label and product taken by the user and verify that the software has extracted correct information. In our case, the operator detects the pricing error, corrects it, and validates the product sheet.

This process of correction and validation of information is crucial, for two reasons. First, it allows, through the intervention of human intelligence, the aggregation and verification of data that will later be used to control external linkage and make the retention rate relevant. This verification can occur at each step of the process and at all hierarchical levels. Once again, photographs find their purpose here: there is no room for doubt or error in your analysis tables.

Secondly, due to the very nature of the Machine Learning principle. This means concretely that the more data the application processes – scans, corrections, etc. – the more effective it will be at processing information. Artificial intelligence thus improves its ability to decipher labels and extract relevant information. It is capable of interpreting label patterns to refine its reading and increase performance. This joint work of intelligences optimizes at all levels the data collection process.

Data collection, a crucial aspect of your competitiveness

The advent of the digital age has shaken up the traditional codes of competitive intelligence. New technologies facilitate the collection of data, from competitors’ websites or directly in stores. A fundamental component of your competitiveness, the exploitation of collected data allows you to adjust your positioning and pricing strategy, in order to increase revenue, margins, price positioning, and market share. Optimix offers, through Scan In Store, a solution for real-time data collection, ergonomic and adapted to the stakes of price reactivity. Scan In Store optimizes the organization of resources necessary for price capture, whether in terms of time or personnel.

Its action, organized concurrently with the other modules of Optimix, allows for your data collections to be placed in an environment dedicated to your price competitiveness. We invite you to contact us for more information or a demonstration.

Editeur de logiciels de Pricing et Supply chain
Pricing and Supply chain software Editor

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