The ways in which retailers use personalization in online marketing have changed dramatically since the early days of the Internet. When we look back, it’s clear we have come a long way, but considering what we know is on the horizon, there’s so much more we can do to take advantage of personalization to improve retail business. How did personalization in online marketing begin and what are some changes we can expect in the New Year?
In its nascent stages, online marketing didn’t allow for personalization. Retailers were simply happy to be able to put up websites, and have an additional way to reach customers on a large- scale basis. But as the Web expanded exponentially, so too did the number of competing sites. It quickly became clear that retailers needed a process or technology with which to personalize their campaigns so they could reach the consumers that mattered most to them. Without personalization, finding the right customer via online marketing was like searching for a needle in a haystack.
Some of the earliest personalization techniques were based on contextual advertising, e.g. giving marketers the opportunity to buy media based on context. “Personalized” information was gleaned through analysis of previous behaviors — seeing, for example, that a customer performed a keyword search for hotels + Puerto Rico. The assumption then followed that the customer might be interested in vacations in Puerto Rico. When that customer next checked their email or favorite news website, they would find an ad for hotels in Puerto Rico shown alongside the news, their emails or as a pop-up ad. In these early days, customer data was limited to information related to their searches or site visits, so each person that performed a search for hotels + Puerto Rico or visited a Puerto Rico vacation site was no different than any other.
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Web analytics marked the next big leap in personalization. By analyzing web traffic, marketers could see patterns, including the number of visitors to a website or the number of page views, and help determine popular trends. More in-depth analysis could provide information on not only what consumers looked at and what they didn’t look at, but also when they dropped off. For example, a retailer could use web analytics to determine what products a customer looked at and how they came to view the product (were they searching or browsing?). When we gained the ability to optimize search engine results, we saw a major shift from contextually-based personalization to data- and audience-based personalization. Search results could be returned to customers specific to their location — down to the city level in many instances — or to their personal search history. All of this data helped retailers organize their web sites and marketing efforts based on the customer’s journey.
We’re now at a juncture where retailers are combining personalization technologies and techniques. For example, marketers can overlay third-party data with their own (first-party) customer data, such as behavioral and demographic insights, for a much more nuanced and multi-dimensional picture of who their buyers are, who is taking action, and when. They can also overlay third-party data to build segmentation models of “look-alike” customers. All these techniques help retailers understand and identify customers before they visit their site, allowing them to filter customers, assign them to “buckets” and treat them to a much more personalized experience.
In the New Year, retailers will be challenged on the personalization front to identify the fragmented set of customers’ touch points — such as mobile, regular display, search, TV, call centers, web site and print — and link them all together in one ID. This single ID can be used to better personalize messages and more precisely target consumers — but most importantly, it can be used to more accurately measure what works. A number of digital marketing providers are on their way to providing such a durable ID, and it’s a race to see who will get there first. Individual media, such as Facebook, Google and Twitter are contenders, as are some demand side platforms and some neutral providers.
In the end, though, marketers will have to leverage their power to move the industry toward the single ID needed for accurate messaging, targeting and measurement. When those pieces are in place, marketers can use single ID measures to learn what works and what doesn’t and apply that knowledge to acquire new customers.
Rob Gatto is SVP, Global Sales for Neustar. He has more than 25 years of experience in the technology industry — managing marketing, sales, distribution channels, and new market development. Gatto is currently senior vice president of media and advertising at Neustar. Prior to Neustar, he was the President of Aggregate Knowledge where he managed sales and strategic accounts.
