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10.27.2021

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SUPERIOR RETAIL EXECUTION WITH IMAGE RECOGNITION

Retail execution and the approach to capturing the in-store conditions have changed many times over the years, in part due to a drive for efficiency and new technologies that have entered the marketplace.

In some businesses, we still encounter the old-fashioned pen and paper being used to record conditions, and we have witnessed product orders being handwritten or telephoned through to a representative of the manufacturer or distributor.

While there is nothing wrong with the pen-and-paper approach, managing the activity on scale does become more challenging, including multiple store visits, numerous reps, and the ever-growing demands to capture new facts of both a FMCG’s own products and competitor information. All of which, if used correctly, can provide a deeper insight into what it takes to succeed at the shelf.

In the new age of technology, there are many different methods and systems that can be used to record and manage in-store conditions. We have the luxury of mobile phones and tablets, which can be used to as a vehicle to populate static or online audits.  Software companies like StayinFront have developed applications with modules that can be configured to meet the needs of different roles and routes to market.

If we break down the basic data that needs to be captured, you begin to understand how much time it takes to record the in-store conditions on both entry and exit. Once the initial data has been captured, a rep would then turn their attention to carrying out improvements in store. Improvements range from merchandising products on the shelf, to selling more products to store owners/managers via enticing pitches to demonstrate the potential return on investment.

Common information we see captured at the shelf include:

    • Inventory Level
    • Product Presence
    • Facings
    • Shelf Location
    • Price
    • Promotions
    • Share of Shelf

Now, imagine having to capture the same information again for competitors. It’s a time-consuming exercise.

So how does a FMCG manufacturer achieve superior execution?

The first requirement is to establish what activities are being carried out in store today and validate them. Do they add value? What additional information is required to help the buying and marketing teams ensure the business is achieving ROI?

Carrying out an end-to-end review of current and future needs will ensure that whichever software is purchased, the field force and their activities are future proofed. Once the requirements are clear, attention is turned towards finding the right service provider. Remember, it’s the future state that you will need. The right provider will have a strong 3-year roadmap, with a clear vision of how the product will evolve and be developed over time. There are many ‘point in time’ solutions in the marketplace that are fit for purpose and may improve today’s ways of working, but in the long run, you will get left behind with dated and limited functionality.

Also, it is important to identify vendors who are utilizing data, AI and machine learning to ensure the guided store visit process can be as effective as possible.

We have seen adoption in image recognition accelerate during 2021, as FMCG companies explore ways to speed up in-store activities and improve accuracy.  Based on the results we are witnessing being accomplished in the field, image recognition is no overnight fad. It’s here to stay and being developed day-by-day to make the process even easier for field teams. To give you an idea:

    • Accuracy using image recognition has increased from 75% to over 96%
    • The time saved on checking critical compliance metrics per store visit has improved 50%
    • Results are published back to the field rep’s device in minutes instead of hours
    • There has been an overall improvement in back-end reporting and visibility of store conditions utilizing images captured in store

For more information on image recognition, or to arrange a demo, visit https://staging.stayinfront.com/contact-us/

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