Personalizing the customer experience is every marketer’s goal. And with good reason: McKinsey recently found that a high-impact recommendation conveying a relevant message is up to 50 times more likely to trigger a purchase than a low-impact one. Think of Homer Simpson being sent a coupon for Duff beer when he is running low; that is the kind of contextual relevance brands can and do achieve through personalization.
The traditional way to accomplish this is through creating multiple customer segments. Homer Simpson might be in a segment called “35 to 44 years old, male, drinks Duff beer in the bar and at home, Springfield Atoms fan” which Duff could use to personalize their offers to people like Homer. That approach worked for a long time, and companies came to rely on generalized demographic segments to successfully focus on their messaging.
But there are pitfalls. One example was recently reported in a New York Times article, which outlined the case of Gillette sending a package intended for 18-year-old men – a “Welcome to Manhood” offer including a free razor and some coupons – to several women and one middle-aged man. This is a clear case of traditional segmentation’s failures, and indicates the need for a more nuanced approach.
On its face, Gillette’s “Welcome to Manhood” promotion is a brilliant piece of marketing designed to encourage brand attachment at a key life moment, and likely works well for Gillette to increase brand loyalty. For the teens who receive it, the messaging is also contextually relevant, which research has shown results in six- to seven-times higher conversion rates than generic messaging.
If you’re depending on traditional customer journeys and broad segments, then it’s unlikely that you will provide the contextually relevant experiences that the modern consumer wants. Like Jennifer Greer, a 50-year-old professor in Alabama, who received Gillette’s “Welcome to Manhood” package in the mail. I don’t know why she was included in Gillette’s marketing blast for this package because RedPoint doesn’t work with Procter & Gamble (Gillette’s parent company), but the fact she did is problematic for a company that is attempting to make its marketing relevant to people’s lives.
At issue is how customer segments are created. Mostly this is done manually, through defining key demographics that should be included and then applying those segments to customer data. As data volumes increase alongside the speed of commerce, however, this approach doesn’t scale efficiently. The modern customer has also shed the generalizations of the past, which were useful because the volume of data consumers generated was so much smaller. Further compounding the issue is that customers now expect individualized experiences that are tailored to their specific interaction history, behaviors, and preferences.
If traditional customer journeys are dead and broad segments are the wrong approach, then how can marketers personalize interactions in the age of the empowered consumer?
The answer lies in automation and intelligence. Marketers need to rethink the way they approach segmenting customers. How many hours of work would it take for a marketer or a team of marketers to manually create two million segments of one? What about the content required to support each message? This approach just does not scale in today’s hyper-personalized world.
Marketers need to embrace analytical approaches that can automatically score and suggest appropriate audiences and content. A simple propensity model can ensure that only customers that possess certain characteristics, whether demographics, spending patterns, or otherwise qualify to be added into a specific campaign. In addition, machine learning technology can choose an optimal set of audiences to conduct an A/B test of content and automate the winning results to a broader group, with elements of personalization brought in for good measure.
Beyond the automation of segmentation, brands need to be more aware of context, cadence, and activity on digital properties. A customer “Hub” approach, like the RedPoint Customer Engagement Hub™, can ensure that a brand can be ready to react with the right information, offer, or message needed at that very millisecond in any channel or touchpoint. This might take into account various data points such as web visits, clicks, opens, transactions, or even social media preferences.
A hub approach to customer engagement provides the integrated data that results in a “single view of the customer,” which empowers marketers with first-, second-, and third-party data combined into a single point of control. By doing this, marketers can leverage best-of-breed channel technologies to automatically determine which message to provide to an individual customer at any given point – even in real time – and be assured that what they send is relevant, timely, and actionable. The rise of zero segment marketing provides an opportunity for marketers to embrace analytics and machine learning to drive more efficient and effective customer experiences. What is your approach to customer segmentation? Are you leveraging automation and analytics in your approach? We want to hear from you.