From Merchandising To Searchandising: BT at the Shopping Cart
Behavioral Insider: Behavioral targeting is seldom discussed in the context of e-commerce as opposed to advertising, but the ATG platform seems to be an extension of behavioral approaches into merchandising, right?
O' Neill: Yes. It's funny. Coming out of a media background first, and then working with an e-commerce and CRM-oriented software firm, I've always been intrigued by how close and yet how far apart advertisers and marketers were in how they understood what they were doing. On the marketing side, the goal has always been called personalization, and on the advertising side the mantra was targeting. And they were treated for the most part in isolation. But though the jargon was different, it's finally becoming clear that the goals of both, to better connect the right people to the right content, are convergent. It's really about creating a targeted online consumer experience.
BI: You've introduced a varied suite of e-marketing-related applications. What is the underlying marketing concept that unifies them?
O'Neill: It's the realization that e-commerce and e-marketing are not just about what happens at the shopping cart before and after customers get there. At the core of the platform, we're introducing an engine for setting up and defining scenarios for relating creative messages to particular patterns of behavior. The premise is that no two click-throughs are exactly alike. People linking to your site from two different places come to your site with different sets of interests and different motivations, and your creatives need to be responsive to those differences. What we've done is to let advertisers automatically serve their offers based on evolving patterns of a shopper's on-site search activity. By linking the customer's information to the merchandiser's catalog and available ad inventory, the engine can specifically target the customer by area of individual interest rather than cater to the entire site demographics.
BI: How does it work?
O'Neill: The goal of the system is to relate each identifiable pattern of search, browsing and shopping behavior. Businesses can analyze their accumulated customer data to help better target their customer base. Information can then be aggregated from what customers voluntarily provide. It can include things like account registration, poll surveys, preference forms, e-commerce wish lists, shopping carts, and orders placed. The system is able to gather through observing what customers do on the site and may include page visits, products viewed, experience flows traversed, and searches. Businesses can study this data to determine who their customers are and can group them into identifiable segments.
If you're a consumer electronics retailer and you know plasma TV buyers require an average of five visits to your site before purchase, you can frame your messaging to plasma TV shoppers based on where they are in the sales cycle, and based on a profile of how shoppers similar in interests and shopping history move toward plasma TV purchases. Beyond that, they can identify different customer segments based on their search emphases. Do they tend to be most interested in the technical details, in comparative price and value, in status and lifestyle? If you can answer those questions, you can radically improve your knowledge about which advertising and which offer to deploy.
BI: Can all this site-specific e-commerce data be deployed in a wider advertising context?
O'Neill: Yes. The engine can recognize when specific customer types visit various other sites on the Web and target a directed campaign toward them.
BI: What kinds of a learning curve do clients need to undergo in utilizing the platform?
O'Neill: On one level, the greatest strength of the product is also the thing about it that challenges us and clients the most. When there's the potential for customizing offers almost infinitely, what do you decide to say? The irony is that the easier it becomes technologically to personalize targeting, the more challenging it becomes to stay creative.
BI: What do you see as the next frontier for behavioral targeting?
O'Neill: The wider use of behavioral data across channels. Just as the artificial boundaries between advertising and e-commerce need to be overcome, so many smart marketers are now seeing customer service as an integral part of marketing, and applying behavioral concepts to things like call centers and product development. The goal is to have a real 360-degree view of customers, incorporating not just the shopping cart but e-mail, live chat with customer representatives and mobile SMS. The most interesting feedback we've gotten so far is from clients who've found that by better targeting they're not only getting more effective offers and higher conversions, but actually using their information to better serve customers by customizing new products and new brands. Those are the companies who really get it. It's less about just focusing on ads than about learning how to refocus your entire marketing and communications ability.