Beyond Personalization 101
Personalization is nothing new to the retail industry. Sales associates have long been encouraged to use a small notebook to keep track of their personal client lists - detailing a customer's personal information, buying habits, preferences and the like. Armed with this information, relationships could be built, and sales associates could more effectively alert customers to relevant specials, sales and promotions.
Today, customers are as likely to interact with a sales associate as a Web site or call center agent at 2 a.m. With the competition often just a click away, and price no longer a deciding factor, it's come down to the customer experience. Delivering a consistent, positive customer experience is what attracts and keeps the customers coming back.
Personalization is one technique smart retailers and catalogers are using to enhance the customer experience.
However, including a customer's name in an e-mail or on a Web page, or mentioning it during a service call does not equal personalization, nor does it truly enhance the customer experience. If this is your approach, expect your results to be less than stellar.
Today's customer-centric economy requires that every customer interaction - regardless of whether it is on the Web, in a store, or via e-mail - be personalized. Using this approach, customers get the right offer to meet their needs at the right time over the right touchpoint. For example:
- When a customer calls into a call center after spending 20 minutes on the Web site looking at PCs, real-time personalization is at work prompting the call center agent to steer the conversation appropriately.
- When an online customer is looking at DVDs online, a banner ad offers a special price on new releases, if the customer appears to be hesitating about completing the sale, free shipping can be offered.
Effective personalization requires an in-depth understanding of your customer: What product categories do they like? What do they dislike? What is their buying history? What are their browsing patterns? Do they only use the Web to interact with our company or do they also call our agents or use our catalog? Do they have brand prefences? How cost-conscious are they? Is this a profitable customer who requires high-touch customer service?
To gain this razor-sharp understanding, retailers must have a personalization engine that is built upon a sophisticated analytic or data mining technology. These superior technologies use advanced algorithms to glean trends, often invisible to even the most sophisticated marketing mind, from reams of data.
The more data a company draws upon for each customer, the more in-depth the analysis, the more accurate the customer profile, and, ultimately, the more likely an offer will be appropriate, relevant and accepted. Smart marketers often supplement their customer database (usually containing information such as buying or service history) with information gathered through surveys, Web clickstream data, and marketing data from outside sources to create a single view of the customer.
But no matter how "in-depth" a customer analysis is, if it fails to be up-to-the-moment, the efforts will fail. For example, if you present a product offer to a customer that they turned down last night, don't expect the results to be good.
With real-time technology, an analysis must happen in less than a second, as a customer interaction is happening. This is the only way to ensure that a customer receives the most relevant products or services at that moment in time.
Taking this in-depth understanding, personalization then uses advanced predictive technologies to determine and deliver precisely targeted cross-sell or up-sell offers, loyalty offers, or targeted content (such as relevant information about the PC a customer is considering) that might just turn a a browser into a buyer. Once again, these recommendations must occur in real-time, at the point of the transaction.
The best personalization tools rely upon a multitude of predictive technologies to help companies personalize interactions and hone their marketing offers:
- Business rules are used to filter out inappropriate offers. For example, don't offer a discount on a CD player to a customer who has already bought a CD player.
- Real Time Mining scores and rates the probability that an offer will be accepted. For example, if a customer just checked out the customer service FAQ portion of the Web site, a window offering the opportunity to "chat with a customer service representative" could be served.
- Collaborative filtering makes predictions based on past purchases from people with similar characteristics. For example, if you're a 35 year old female buying muffin tins, collaborative filtering will offer up the suggestion that you check out loaf pans because people like you have, in the past, also bought loaf pans.
As retailers develop their personalization capabilities, they must protect customer data. Customers don't want to think that their information is going to be used against them, or worse yet, sold to another marketer. When you gather personal information, you need to reassure customers that the data will not be shared -- consumers want to protect their privacy and need assurance that personal information will remain secure. Assure them that you request this information only to provide better customer service. Once customers realize the benefits of these personalized interactions, they'll readily offer relevant personal details. You must uphold your part of the bargain and develop truly personalized service.
Today, personalization can deliver a host of benefits that retailers and catalogers require to be successful in today's demanding economy:
- It allows retailers to present a consistent face, and offer consistent treatment, across all the channels a customer may choose
- It is a key contributor to customer satisfaction and loyalty
- It enables retailers to increase order size
- It helps retailers close sales and reduce shopping cart abandonment
- It encourages repeat orders