For example, in a 2016 survey of more than 1,500 US and UK consumers by Accenture Interactive, almost two-thirds (65%) of respondents said they are more likely to make a purchase from a retailer that sends them relevant and personalized offers. For example, in a 2014 survey by Adobe, 71% of consumers said they like receiving personalized offers, but 20% reported that offers are not done well, and another 20% said that personalization efforts are too intrusive. It’s as if we marketers believe that the effectiveness of personalization comes from telling the customer or prospect what we know about him or her. In most cases, however, the best way to personalize a marketing message or offer is to make the personalization invisible to the recipient. What our customers and prospects really want are offers and messages that are relevant to their interests and needs. I strongly recommend that you read Mr. Duhigg’s article if you’re involved in developing personalized marketing programs.) Target’s marketers wanted this information because they believed if they could entice a pregnant customer to purchase pregnancy- and baby-related products at Target, she would also buy other products and form the habit of shopping at Target. Specifically, they were concerned about how a customer would react if she received marketing offers that expressly mentioned the pregnancy or otherwise indicated that Target “knew” she was pregnant, even if she had never told Target about the pregnancy. This example makes three important points: First, data and predictive analytics can enable marketers to develop marketing messages and offers that are highly relevant for individual customers. Second, relevance alone is not enough to ensure that personalized marketing messages will be effective and well-received.
Marketers in virtually all kinds of companies have become intensely focused on improving the quality of the customer experience. Most marketers have long believed that personalizing offers and messages for individual customers is critical to delivering outstanding customer experiences. As a result, marketers are continuing to make personalization a major priority.
In the 2017 Digital Trends study by Econsultancy (published in association with Adobe), survey respondents identified targeting and personalization as one of their top three “digital-related” priorities for 2017, and 51% of company respondents said they will increase their spending on personalization this year.
Numerous research studies have shown that personalized marketing can be highly effective. For example, in a 2016 survey of more than 1,500 US and UK consumers by Accenture Interactive, almost two-thirds (65%) of respondents said they are more likely to make a purchase from a retailer that sends them relevant and personalized offers.
It’s also clear, however, that many customers aren’t particularly impressed by the personalization efforts they encounter. For example, in a 2014 survey by Adobe, 71% of consumers said they like receiving personalized offers, but 20% reported that offers are not done well, and another 20% said that personalization efforts are too intrusive.
For several years, the most common way to personalize a marketing message has been to include specific facts about the recipient – name, job title, company affiliation, etc. – in the message. I call this explicit or overt personalization. It’s as if we marketers believe that the effectiveness of personalization comes from telling the customer or prospect what we know about him or her. That may have been true in the past when personalization was still novel, but today, most types of overt personalization are not effective.
There are, of course, notable exceptions. For example, I find the product recommendations made by Amazon to be useful and valuable. They frequently alert me to the availability of recently-published books that I didn’t know about. Amazon’s website clearly states that recommendations for me are based on the items I have previously purchased or the items I have recently viewed, and Amazon even enables me to customize the factors that are used to create the recommendations. This is an example of explicit personalization that is still very…
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