For my birthday, I got a Yogurt cup full of chocolates…

It was a joke, of course. I had 25 people over for a fantastic evening, and a friend (who once had the misfortune of asking me what I did) got the yogurt because she could no longer walk into a supermarket without looking up at the cameras.

And,

Thank you to those who participated in the “Amplify Store Sales” workshops.

It was fun.

Today, I’d like to share a case study from the workshop.

Here is how you connect the stories of yogurt and switching behaviors with the step-by-step framework of PEACE for Profit.

You start with a goal.

For example,

A Category Manager wants to increase shelf sales by 5% by tracking Switching Behaviors with Computer Vision.

Yes, that is the…

Win-Win-Win Alignment

The [business user] wants to achieve [outcome] by managing [behavior] with [technology solution]

The next step is the PEACE for Profit framework.

Identify Behaviors:

People who visit the yogurt display in a supermarket and want to switch yogurts stay longer in front of the display because they read two or more labels of yogurt products.

Quantify Behaviors

The relevant metrics for the behavior are:

• # of people who exhibit Switching Behaviors
• # of Visitors in Yogurt Zone (by period)
• Stay Time is > 180 seconds (3 minutes)
• # of mini-locations points per person (depends on technology)
• % of Switching Behavior out of Sum Behaviors.

Identify Context

The decision to buy a new yogurt brand depends on complementing and competing yogurts on the display. Therefore, product planograms significantly impact “why we buy.”

In addition, the real-time local environment plays a role. And you want to identify the triggers that will influence Switching Behaviors.

Quantify Context

The relevant metrics for insights on the local environment are:

• # of people in proximity who “see” yogurts on a shelf (attention and complexity metrics)
• # of zone footfall and in proximity zones (Real-Time Demand)
• Stay Time segmented by period and planograms (Attention Metrics and distribution curves)
• # footfall, purchase sales conversions. (CTA Funnel)
• % Switching Rates by Segments and Periods.

Store Experiments

Next, you design in-store experiments to test your hypothesis.

• Replacing the High Sugar Vanilla Yogurt with Plain Greek Yogurt will increase sales in the yogurt category.
• Test new yogurt displays in 4 to 10 stores (different locations) + 1 control store.
• Run the test for a minimum of 12 weeks (to achieve 10,000 data points for statistical significance in the results).
• Call-to-Action: Get a 1% uplift in Sales Conversions for yogurts.
• Success KPI: Get a 5% annual sales lift for the yogurt category.

And you put it all together in the framework:

Cool.

In the following weeks, I’ll share more case studies.

If you want me to address your challenge in the newsletters, define your Win-Win-Win Alignment.

Cheers,

Ronny Max

P.S. Want to increase Store Sales and Performance? Want to apply the PEACE for Profit? Start with the Win-Win-Win Alignment.

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Behavior Analytics Academy trains people and teams to increase conversions, sales, and profits in physical environments. Build Profitable Ecosystems.

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