Identifying Offline Clicks and your In-store Pick-through Rate (PTR)
What is an Offline Click?
Consider the insights your digital click-through rates (websites, emails, search and social ads, etc.) provide your marketing team. They help identify customer interest and allow you to build personas for your shoppers to supplement their purchase data. Now, what if you could identify when an in-store shopper is interested in a product but does not make the purchase—yielding no data points on their visit?
With “Offline Clicks” you can now gather in-store customer interest and intent data just as you do online. These analytics provide both retailers and their brands previously unidentifiable insights into offline customer product interactions as well as a new set of KPIs to help retailers make better data-driven product placement decisions. Build detailed reports for marketing and brand partners and capitalize on the aggregate product interaction data for regional offline-to-online re-targeting campaigns.
A customer picks up an item. You know about it in real-time. Place a sensor in a shoe or on a hanger—in a cooler or on a hockey stick—and know when it has been moved—enabling you to identify the “Pick-through Rate” (PTR) of your physical store’s products. You can identify which products were interacted with as well as the exact date and time of each interaction, providing deep data insights and visualized reporting for your marketing team to act upon.
How Does It Work?
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Small sensors are placed inside or attached to display item. (In this use case, shoes.)
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Sensors detect date, time and location of when a shopper picks up a shoe.
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The shoe interaction data is relayed to our cloud dashboard in real-time.
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Reports (and alerts) are created for specific shoe displays over defined period(s) of time.
Sample Data
The following slides provide sample data from shoe wall interactions collected over time—identifying the “Pick-through Rate (PTR)” for your in-store products. These are only a few of the many reports you can create by manipulating the massive data-set from potentially millions of annual product interactions across all of your physical store properties.
Additional Integration Possibilities
Aggregate Product Data
Put a beacon in/on any product and gain insights. Whether it's a long-term installation or a short-term study, there are consumer insights we can provide that, to this day, are not being evaluated in retail. No salesperson is counting how many times shoppers are interacting with products and reporting that manually. They may have a sense, but the data we can provide will be concrete. Think of the value not just to you as the retailer, but to your brands as well. Store locations could offer this "in-store consumer insights reports" to their brand partners as a courtesy or as an add-on offering funded by the brand. This technology can also be used for real-time, in-store customer service initiatives.
Mobile Proximity Marketing
Integrate an SDK into your store's native app to gain one-to-one insights by matching in-store, shopper-specific dwell time and location (or proximity RSSI) with date/time of product interaction to match product with shopper for offline-to-online re-targeting. It can go as far to be connected to your POS system so that the consumer would not be re-targeted if they actually purchased that item on that visit. This is a way to utilize mobile to improve the shopper-experience without inundating them with irrelevant lock-screen notifications—in turn warding off app abandonment.
Interactive Customer Experience
By integrating a SDK into a native app, we can send product-specific content to the user's mobile device to provide a rich media experience based on the product they are holding. (i.e. The shopper picks up a Nike running shoe and with the app open, receives detailed information their device’s screen for them to review, favorite, share, purchase, etc.)
Product interactions can yield more than just data. We also have an app that allows for rich media product info to be triggered to a nearby display (tablet, monitor) based on which product was picked-up to create memorable customer experiences.