Marketing Bootcamp

Get Personal to Close the Customer Experience Gap

Get Personal to Close the Customer Experience Gap
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Over the past few years, there’s been a tremendous shift in the marketing world. Consumers are more educated than ever before getting to the purchase stage thanks to multiple access points that provide not only information but serve as an outlet for voicing feedback, both good and bad.

As a result, marketers can no longer get away with irrelevant and disjointed communication with customers. A recent study from IBM found that four out of five consumers don’t feel that brands really know them. With so much data at a company’s disposal, this should not be the case. Information about customers is available through social media, mobile and Internet in addition to a company’s internal systems -- call centers, customer relationship management, transactions, etc. But what good is all this data if marketers are not effectively learning from and acting on it to deliver personalized, relevant experiences?

Related: The Power of Persuasion: Using Brain Science to Get Users to Act

To do this, marketers need to understand their customers on a deeper, more personal level. They need to focus on the elements that go into customer decision-making, because it has a direct correlation to increasing loyalty -- the gateway to revenue. This involves not only finding the right insight, but also acting on it at the right moment. 

Over the last year, I’ve spoken with a number of marketing executives on how to provide enhanced customer experiences that drive loyalty and reduce churn. Here are some personalization tactics organizations are using: 

1. Put the customer at the center.

The most successful companies are those that don’t just put their customers first, they put them at the center of everything. As soon as a customer begins interacting with your company through any channel -- whether it’s a store visit, customer service call or website inquiry -- create an individual customer identity in your database. This allows you to track what users do each time they interact with your brand so you can better understand them on an individual level and then tailor your marketing initiatives to their specific needs.

By understanding customers on this level, you can answer critical questions like how did they initially find your company? When and from where did they visit your website? Do they act in different ways on different channels? Knowing these answers will help you achieve more targeted campaigns that engage and motivate both prospects and customers.

Netflix is a great example of a company with this mentality. What they do, on paper, is simple. Netflix builds an individual profile of each customer as soon as he or she signs up, based on the information they share when perusing the website. As the customer becomes more and more active, Netflix gets smarter and continually profiles each customer against their database.

According to the company’s blog, Netflix has a number of algorithms for personalization and recommendation including how to rank videos in each row and how to create meaningful groupings of videos that help the customer process their choices on the home screen. As a result, Netflix is renowned for its personalization process, and is one of the most popular brands out there.

Related: What Your Business Can Learn About Leveraging Big Data From Netflix, Eloqua and the 2008 Election

2. Focus on the long-term customer lifetime value. 

A lot of companies put more prestige on acquiring new customers, when retaining the ones you have is more cost efficient and has higher potential for revenue. This is why you need to pay attention to maximizing the customer lifetime value (CLV) through a personal approach.

Amazon is a perfect example of a company using CLV effectively. The company places a strong focus on converting non-prime members to paid prime members through personalized algorithms.

Amazon recognized that once these customers join, they are more engaged and buy across more categories they hadn’t previously, maximizing their customers’ lifetime spending potential. The company points out that Amazon prime members spend nearly triple what non-prime customers do. They also tend to write more positive reviews, which Amazon then leverages when developing algorithms for target shoppers whose spending patterns indicate they are influenced by positive customer reviews, thus increasing spend potential.

3. De-clutter your data. 

Most companies are overwhelmed by the sheer volume of the data they possess, much of which is irrelevant to the mission at hand and is just taking up space in the database. By determining which parameters will have the most impact for your company, you’ll be able to make better use of the data you have through a more focused approach, rather than attempting to sort through it all.

To start, map out your goals, and get as specific as possible. Using Amazon as an example, they might say, “I want to convert 23 percent of customers to paid memberships this year.” Through machine learning, Amazon can focus on the data that will actually make a difference, such as how much someone has spent on shipping as a non-paid member, their purchase volume in the year, their location, how and when they order, etc.

Once those are understood, Amazon can alert the customer that a prime membership will actually save them money over the course of the year. If they also know that this customer interacts most with Amazon on her mobile app during the evenings between 6 and 8 p.m., they also know that’s when she’ll be most likely to react to an offer at a time and way that is most relevant to her.

Data will continue to propagate and get bigger, but that in and of itself is not enough. We as marketers need to turn raw data into actionable intelligence by focusing on the relevant data, gaining insights and generating action from it. Only then will marketers consistently produce loyal and profitable customer experiences. 

Related: All Prime Members Now Have Access to Amazon's Press-to-Buy Dash Buttons