Amazon's New In-Store Analytics Foreshadows The Future Of Shopper Marketing Retail Analytics

According to an Amazon Blog post, they have launched a new analytics platform for brands to better understand how shoppers interact with products in AmazonGo enabled stores.   This is exactly the vision of Perch’s Shopper Marketing Cloud and Analytics Platform.   “With Store Analytics, brands will have access to details on how their products are discovered, considered, and purchased in applicable stores to help them inform decisions related to selection, promotions, and ad campaigns. Through the secure Store Analytics dashboard, brands can access aggregated and anonymized data about how their products rank and perform. Additionally, advertisers running in-store campaigns such as digital signage will see associated performance metrics in their ad campaign reports.

But what it tells us about the future of in-store analytics and how it can change the way we think about influencing the customer journey is profound - and we know this here at Perch because this is exactly what we have been working on in our at-the-shelf analytics with Shopper Marketing Cloud.

Full Funnel Visibility With At-The-Shelf Retail Analytics

Raydiant Retailer and Brand Middle Of The Funnel Analytics

Right now, brands are flying blind. They may have estimates of general store traffic, but now how many shoppers go to each category, let alone how many shoppers pass by their displays. They don’t know if their displays are effective in attracting shoppers to the shelf. And they don’t know how they interact with the products on the shelf and how design elements or digital content change shopper behavior. We are only beginning to look at sales lift data as grocers launch performance marketing groups to share SKU level sales data by store and time in a way that is helpful (mostly to fund their growing retail media network monetization at this point).

We at Perch believe there is an in-store analytics revolution is coming. Retail traffic and basic flow heat maps are nice, but they are still basic top of the funnel. Think about stores or the retail shelf where your products are as an eCommerce site. Currently we are managing it based on unique users (store traffic) and bottom of the funnel sales, without any idea of what people are “clicking” on and exploring at the shelf. No idea of where on your site they go, what products they click on (pickup) and what content or design changes their behavior!!!

Could you imagine trying to optimize your eCommerce site with no click data, demographic data, dwell times, or A-B testing, etc.? That would be crazy yet here we are doing the same where 85% of retail sales occur - in-store! The future oh physical retail analytics is a full funnel understanding of how shopper marketing tactics affect the shopper journey.

What Can You Measure With At-The-Shelf Retail Analytics And What Decisions Can You Make?

Raydiant Conversion Optimization Behavioral Metrics

So thinking about pickups as “clicks” at the shelf, pickups are the key to unlocking visibility. How do customers actually interact with planogram designs and how do designs change product shopping behavior? How does pricing or promotions change the way people click at the shelf? How can content change which products shoppers interact with? Can the right message increase discovery? Yes! Can the right message increase conversion rate from pickup to sale? Yes! Can the right message drive cross-sell to another product? Yes! Which content does that? Well you need the very at-the-shelf retail analytics that measures the clicks at the shelf.

Do We Have To Wait For Cashierless Checkout To Measure At-The-Shelf Retail Analytics?

Cashierless checkout brings a range of understanding of what people are pickup up and putting down and does so on a storewide basis. But it’s currently wickedly expensive from an Opex perspective and the technology is immature. AmazonGo technology uses both computer vision and weight sensors. Walmart insiders have told me that certain items like towels will require RFID. Cashierless checkout in 2021 was in just above 80 stores and looking to triple in 2022 to over 280. It is expected to grow 90% YoY for next 5 years, but that still is only about 2700 stores by 2027. So it’s going to be a long time before we see cashierless checkout widely adopted.

In the near-term, retailers and brands don’t have to wait so long to start getting visibilities in key categories. In grocery, these may be high margin or value categories like pet, beauty, health and baby. At big box retail, it might be similar categories, as well as electronics, video games and toys. In home goods, it might be appliances, cookware, shelving design and more. And the best part is that this can and will be paid for by brands if there is an opportunity to drive sales lift, as with interactive retail display. With premium retail media network opportunities linked to at-the-shelf data, the cost of retail analytics is not only fully subsidized by brand trade dollars, but earn 4-5x, including pulling digital ad dollars from brands to physical store locations, a key opportunity for retail media networks.

The future of retail media and shopper analytics is coming quickly. Brands and retailers have the opportunity to implement now without the extraordinary costs of cashierless checkout like Amazon Go. And we are seeing it now and at scale with Perch’s Shopper Marketing Cloud retail analytics.