Use Offline Data to Improve the Customer Experience

Use Offline Data to Improve the Customer Experience

Online retail stores like Amazon and Warby Parker have recently established brick-and-mortar stores to provide physical presences for their online customers. Of course, one of the reasons consumers might enjoy having physical stores available to them is the convenience of being able to buy products online and return them in-store if needed. But, this isn’t the primary reason an online retailer like Amazon would create a physical presence for its customers. A brick-and-mortar store opens more possibilities for omnichannel transactions, offline data collection, improved supply chain, and ultimately, better online and offline customer experiences.

Collecting Offline Data
In addition to the data collected online, stores like Warby Parker or fashion retailer Brooks Brothers can monitor traffic patterns through their stores. For many years, Brooks Brothers had its own somewhat informal way of tracking the types of suits, shirts, or ties its customers wore. But now, more systems are available that revolve around both collecting the types of data that come from direct transactions with consumers and revealing the behaviors of intent to buy. We are now able to build the digital profile.

One type of data that marketers can collect from physical stores is dwell time. If a customer is engaged in a particular area of a store, how is he spending that time? Is the experience good, bad, or indifferent? Is he trying to move from one location to another? Is it taking him too long to find what he wants, or is there some type of engaging experience within that particular location of the store that’s driving traffic? Technology has evolved in such a way that store operators who have had the ability to use store trackers to monitor things — such as the moment somebody enters the store and how traffic flows in and out at any given time — now have more granular datasets that enable them to track how long the volume of the store is trafficked within a 60-minute timeframe or that a high percentage of customers stood in a particular department and in front of a specific display.

Challenges of Offline Data
The challenge of offline retail data is that it is transaction-rich but intent-poor. Ninety-two percent of sales go through physical retail channels, but you lose much of the intent data that you get from things like page views, search terms, and how many times somebody linked from a particular blog page.

While not used extensively due to cost and infrastructure challenges, some stores are using RFID (radio-frequency identification) technology on their products. Originally used for loss prevention, the technology enables retailers to track how many times consumers pick up a product or even whether the product was picked up, purchased, and taken from the store, giving retailers a true image of conversion — but, it still isn’t practical across all product categories. It may be feasible on a $500 jacket, but will consumers spend an additional $.011 per box of cereal? So, while the technology provides many possibilities, we have yet to overcome some of the challenges because RFID has still only been applied to a small percentage of all the products in the marketplace.

Other ways of collecting offline data include iBeacons and near-field communications (NFCs), which allow companies to track the offline behaviors of customers who have opted into a brand’s marketing-communications program. Of course, these types of technologies come with privacy concerns. Many audiences are uncomfortable with companies tracking their movements this way. Therefore, the sample of data can be limited. However, it can provide great insights into the patterns and behaviors of your best customers.

Using Data to Improve the Customer Experience
Ultimately, however, the data collected — whether online or offline — is about shaping the customer experience. Marketers can use this data to consider how they want to present products through the customer-experience flow. For example, grocery stores often put the dairy section in the back of the store because, if customers want to pick up some milk (what many people visit the grocery store for), they want them to walk through the entire store so they see all the different products before they reach the dairy section. The data collected can inform them of what they want their customers to see as they make their ways to the products they came to buy.

Convenience is another factor in the customer-experience chain. Through their Cartwheel app, Target is now giving customers the ability to create and save shopping lists. Then, the app guides customers through the store to the products on their lists, improving efficiency and helping customers get in and out of the store in less time.

From a store-operations perspective, the data can also inform and help store management and operations in terms of departmental support and staff management. Of course, this is going to be more relevant to a big-box, larger-footprint retailer.

Leveraging Offline Data for the Online Experience
Offline data can also be leveraged to enrich the online experience, where the online experience — while it has its nuances and benefits from a convenience standpoint — is challenged with regard to product interaction and shopping environment; sight, sound, and smell. Marketers need to make sure the customer experience is seamless between all channels.

For instance, if a customer visits a brick-and-mortar store on the weekend, and then visits the website or receives a communication from its email program on Tuesday morning, those interactions should complement one another. Something as simple as a postcard can drive an online/offline campaign, connecting online customers to brick-and-mortar stores and vice versa.

While offline data has traditionally been more difficult to accurately track, it’s easy to see that we are at an interesting point with technology in which we can better understand consumer behaviors in physical retail locations by combining online technology with in-store action.

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