Contextual Retail: Insight at the Point of Action -- Full Text

Customers have evolved their shopping practices and use multiple channels to search, compare and purchase products and services. For example, of the 40% of consumers who own smartphones, 70% use them while shopping in stores (Google & IPSOS OTX, April 2011). While online shopping sites provide an array of tools that help customers gain insight during the purchase decision process, retailers provide few such tools in stores.

Customers are turning to their own devices to support decision-making in stores, and as such smartphones are becoming an integral part of the shopping experience. The next big challenge for retail is to determine how to use smartphones to engage with customers and drive purchasing by providing key insight during the purchase decision process. Retailers who can provide effective decision-making tools for in-store customers will open up a new channel through which to market and sell.

Traditionally retail technologies have focused on providing business insight to store management. Now that customers are entering stores with technology in-hand, the focus must expand to providing product insight to the customer as well. By providing customers with product insight, retailers can provide a differentiated experience that increases loyalty, which can in turn increase revenue.

How do you provide insight during the purchase decision process? By determining a customer’s context and leveraging that knowledge to provide a customized in-store shopping experience. While customer databases can show what a customer’s purchase patterns are, they say little about who the customer is and what they are trying to achieve. Customer databases provide a view into people who decided to purchase but miss the potential customer who wanted to purchase, visited your store, and left without buying. To better serve customers and increase sales, retailers will need to learn more about who their customers are, what their needs are, and provide them with relevant insight into the products and services available.

Accenture has developed an approach to providing customers with insight that involves combining new forms of customer data with traditional forms and leveraging this new view of the customer to create a set of services to aid the purchase decision process.

This approach uses a combination of social media profile data, customer purchase history, and customer behavior logs as forms of context to describe customers. Social profile data provides a much more descriptive and accurate profile of customers and is a largely untapped source of information. Although customer behaviors are tracked online, routinely very little information is collected about customer behaviors in stores. Combining social profile and customer behavior data with customer purchase history can create a rich picture of the customer, which retailers can use to better segment customers.

Based on those segments, decision support services can be created for customers which would (1) help them find the right product and customize that product to their needs, (2) offer more than a sales experience, but a service that places shopping support in the palm of the customer’s hand, and (3) establish a new channel that enables direct communication with the retailer. This channel would allow retailers to learn more about the customer continually, and tune the in-store experience accordingly.

What is context?
We define context in retail as any information that characterizes a person and their past and current interactions with other people and technology at any point in the purchase decision process. In other words, retail context is comprised of a customer description (e.g., age, interests, and gender), past interactions with the retailer, and a description of the customers’ purchase environment (e.g., availability of friends, devices available, location, product being viewed, etc.).

Insight Powered by Context
Increased “showrooming”―using the physical store to explore the merchandise and subsequently purchasing from the online vendor with the cheapest price―suggests customers are not being engaged in physical stores. As a retailer, you can reclaim your customers by engaging with them as they search and evaluate products in store. The first step in our approach is learning who the customer is. Social profiles provide data including gender, employment history, educational background, hobbies, and interests (including TV series, movies, brands, etc.). This contextual information can be used to make inferences about what types of information and products would be of interest to a customer. Logging the actions of customers while they are in the store can further enhance this data. The next step in our approach involves using this enhanced awareness of the customer to create services that support decision-making in the physical store. For example, a tailored experience can be crafted to engage the customer while in store and support her through the stages of the purchase decision process from awareness to purchase. A few strategies to accomplish include:

• Personalizing product content

• Using the activities and sentiment of friends (and similar people) to filter product choices and provide opinions

• Providing access to social networks to solicit opinions

By engaging customers in these ways, you open a new channel for communication, which can be used to drive sales and increase trust. Each of these strategies can be integrated into a service you can make available to your customers.

Services Based on Insight

Personalized Product Content
Retail stores currently provide a consistent experience across customers. Every customer that comes into the store is presented with the same physical space, same information and same products. Furthermore, customers are exposed to all products even though not all of them are relevant. By making the store experience more personal, the customer can better navigate product choices and feel more confident about making purchases in the store.

Smartphones provide a mechanism by which an experience meant for everyone can be personalized with little change to the physical store. Many retailers already provide their customers with mobile apps for their smartphones. By using Facebook Connect^TM as a login service for the app, the smartphone can be used to collect social profile data to learn more about the customer. With this context, a customer can be classified into one of a few pre-defined customer segments. For each segment, a custom experience can be designed to address the needs of customers in that segment. Technologies such as augmented reality and QR Codes can be used in the physical store to connect physical products with digital content that is tuned to the user’s needs.

The smartphone can also be used to collect data on the customer’s browsing behavior. This information can be combined with social profile data and purchase history to further personalize the experience. For example, consider a customer in the market for a new TV. Given her Facebook interests in music, movies and gaming, and her recent online browsing of smart TVs, the TV descriptions displayed in the retailer’s smartphone app could be tuned to highlight relevant features. This could include displaying the movie and music streaming apps available, and the suitability of the display and audio for gaming and movie watching.

Using this strategy, the customer benefits from a more personalized shopping experience and gets the support needed to reach a purchase decision in-store. In exchange for some personal information, customers can access an experience that surpasses the traditional one. This can take the form of relevant recommendations, ratings, information presented in the most easily consumable form, access to the experiences of friends, and more.

For its part, the retailer gets to differentiate itself from its competitors and increase customer loyalty. The use of a smartphone as a shopping tool in the store provides retailers with access to the behaviors of customers and insight into how they interact with products. This data can be used to make decisions about store configurations and associated product placements. Providing a valued custom service opens up access to a wealth of information that retailers have traditionally found difficult to collect.

Although more information about customers can certainly be useful, retailers must tread carefully where customers’ personal data are involved. Some customers may be quite reluctant to provide this type of information to the store, so retailers must avoid asking for more data than they need and must take every measure to protect the customer’s privacy. By earning the customer’s trust, retailers can enhance the customer experience while increasing their ability to sell. A reputation for sloppy handling of customers’ data is one of the fastest ways to at a minimum damage relationships with individual customers and even worse the public at large.

Highlighting Relevant Products
The opinions of those we trust often influence our purchase behavior, and social network sites make it much easier to obtain those opinions. To help reduce the overwhelming variety of products, social networks can be used to bring products that are relevant for a customer to the forefront by highlighting the products explored by friends. When a customer decides to retrieve information about a product using a physical tag in the store, rather than show product recommendations based on the general population, a retailer could show a listing of products that people in the customer’s social graph have browsed, liked, or purchased. Not only does the customer receive information about how friends rate the product scanned, but she is exposed to other relevant products.

Because of the way social media groups people, you can further increase the relevance of opinions by separating friends into relevant subgroups (e.g., work friends, tech friends, hiking friends). Using subgroups will help customers to filter products based on the relevance of friends to a particular product purchase. For example, an avid hiker may want to see only the hiking shoes her hiking group has liked, browsed or purchased as opposed to seeing the same for her work friends.

While it’s useful for the customer to know what friends think, there are cases in which the customer’s friends may not have shared their opinions. In such situations, it’s useful to have an overall picture of how people similar to the customer feel about a particular product. In this case, the customer’s social profile can be used to find social “doubles,” or similar people who have provided feedback on the product. This provides a measure of the “buzz” around that product based on similar people. Whether highlighting relevant products using all friends, subgroups of friends or people who are similar to the customer, using social media and purchase behavior logs can help filter the expansive set of product alternatives down to a manageable level for the customer.

For the retailer, highlighting products based on friends’ interactions or the interactions of people who have similar purchasing history provide a method for predicting what the customer will look at in the store. This data can be used to fine-tune product recommendations and offers. Additionally, customers who look at those products in the store provide clues about what they find interesting. This information can be used to determine where hotspots and dead spots exist in the store. To better handle hotspots, management may want to deploy more associates to that area. For dead spots, management could put effort into developing strategies to generate more buzz and drive more interest toward those products.

Easy Access to Feedback
Most of the feedback we’ve discussed so far has been “implicit,” meaning that the activities of others are provided to customers as a gauge for opinions about that product without any explicit effort on the customer’s part. An additional strategy involves providing “explicit” mechanisms for customers to reach out to their social networks to get direct feedback and recommendations. Retailers could enable Tweeting, Facebooking, and posting products to other social media directly from the store. This provides additional insight to help the customer make a decision at the point of purchase.

For retailers, there’s an inherent benefit when customers solicit feedback because they’re making others in their networks aware of attractive products that the retailer sells. Social network users often make requests of their entire network, although only a limited set of people may be able to provide useful feedback. As a result, customers could potentially nudge others into considering the same or similar products, thereby increasing the retailer’s reach.

Conclusion

In general context can be used to enhance user experiences. For retail, context gathered in-store can help personalize product content, highlight relevant products and provide easy access to feedback from peers. The result is an improved shopping experience and deeper ties between the retailer and customer. Understanding customers’ behavior in the actual store helps bridge the in-store and online channels, providing a seamless retail experience.

No matter what the industry sector, the use of a customer’s context and activity (historical and current) can help to significantly improve the purchase experience. Using contextual data in other arenas requires identifying relevant information and using that information to provide additional benefits to stakeholders. Technology now enables the capture of all sorts of context. The time is right for using context to provide breakthrough innovation in customer services.