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Marketers know that data-driven personalization represents a huge opportunity and a meaningful way to meet customer expectations.
Studies back up this common sense. In a recent study, 89% of decision makers said that personalization “will be invaluable to the success of their company over the next three years.”
Yet most organizations struggle to personalize content. I explained some of the reasons why in a recent episode of Live With CMI. Read on for the highlights or watch the video interview:
You are missing the right data (or you don’t have access to it)
You know you need to offer personalized recommendations on content, products, use cases, etc. But you may only be able to do this at a high level of segmentation (if at all) because you lack the data to enable the personalization that matters to your audience.
This obstacle arises when you do not have an integrated data system or do not have enough data. Your organization probably looks at data in an ad hoc way:
- The customer relationship data is held by the sales team.
- The website data is held by the technical team.
- Customer service details are held by the customer support team.
All of this information is stored in silos, and without bringing it together, it is impossible to create a holistic view of the customer that the marketing team can use to align its goals and needs.
You have no say in the data infrastructure or collection
As marketers, we explain why our brand is relevant and a good fit for the customer. That's why in B2B and B2C companies, marketers are the ones who need to know their customers and prospects best.
This means you (or someone on the marketing team) needs to have a seat at the data table. Marketing should drive the strategy behind the company's data collection, infrastructure and use.
Customers expect brands to give them highly relevant information. According to a 2023 survey I conducted with Researchscape for my book, most people (88%) expect brands to interact with them based on their previous relationship with that brand. A similar number (85%) of people expect brands to give them personalized recommendations.
This is no surprise. Anyone who has ever shopped on Amazon or watched shows on Netflix knows that a brand can recommend things based on past consumption habits. Imagine having to reprogram Netflix every time to suit your preferences. That would be a terrible customer experience.
Years ago, Todd Yellin (then Vice President of Innovation at Netflix) said in an interview with TechCrunch that their goal was to know the viewer so well that with the press of a button they could play them exactly the show they wanted to watch at that very second.
Customers want companies to make everything that easy. But to realize this vision, marketers must develop a data strategy because they can ask questions that help determine how data should be collected.
If you don't have a strong say in how the company invests in data infrastructure, how the data is used, and how you tell the data story to your customers to build trust, then you lack the ability to control your own destiny.
You overlook this important data
When thinking about what information to collect about your prospects, consider some commonly overlooked data points. Behavioral, technographic and psychographic data are dramatically underused.
By behavioral data, I don't mean how often someone shops with you or how much they spend. I mean:
- Where do they consume content?
- Which content leads you to further content?
- How often do they interact with you for support?
- How often do they interact with each other to learn more about the industry?
You want a holistic view of customer behavior, not just while using your product.
Many B2B companies should consider technographics – the technology stack that relates to your brand’s space.
For example, if you work for Zapier, the automation tool that connects web apps and services, you'll want to know which customers are connecting to your tool. The data analytics team should track that. Knowing the buyers' tech stack will tell you, for example, which additional connections to enable.
Technographic data is also valuable in the B2C space. If you work for a video game company, you'll want to know what headphones or accessories your customers use. A company like Apple will want to know what other types of tools customers are likely to use together. This data can help you anticipate your customers' needs.
Psychographic data includes the attitudes and motivations of your customers that determine what's important to them. Think about how people shop online. Someone who values a good deal might look for sites that offer free shipping or a discount for an annual (as opposed to monthly) subscription.
Other customers aren't necessarily looking for added value. They're more concerned with ease of use. They want to hear a story about how easy it is to learn, the support available, or how you're making their lives easier.
Everyone has different motivations. By working with your data analytics team to gather information about those motivations, you can tailor the messaging on your landing pages, emails, and all other communications. Someone who values value will receive one message, and someone who values ease of use will receive another. It's a more effective marketing approach—you're not wasting time delivering an irrelevant message.
Ultimately, you need to determine the right mix of data your company should collect. You shouldn't collect every single piece of data, as this can overwhelm your team. And if you ask for too much data, it will be inconvenient for customers.
Show potential customers the benefits they will get from sharing data
Privacy plays a big role in personalization. It is possible to collect data and use it in a transparent way without scaring people away.
Several brands ask people about their preferences in a way that builds trust. For example, some brands offer the option to stop receiving messages on Mother's Day, as this can be a sensitive time of year for some customers.
Questions like these create a customer preference profile for the marketer, but also build respect and trust among the customer.
Some companies do a good job of explaining what data they collect and how they use it. Lemonade, an insurance company, is a good example. They are clear about what they do and don't do with their customers' data. Their privacy policy is written in a human and easy-to-understand way. They want customers to trust that Lemonade will not do anything wrong with their data.
When asked about their preferred balance between privacy and personalization, about 50% of consumers say they are okay with having their data used for more personalized services and experiences, according to a recent PwC study.
People recognize the trade-off. Since they receive more messages than ever before, many appreciate companies that give them recommendations that save them time.
For example, as a mother of a young child, I appreciate when Amazon recommends clothing sizes based on the last time I purchased the item. If I bought a 12-month size six months ago, Amazon will recommend an 18-month size the next time I shop.
This saves me time because I'm less likely to order the wrong size. It saves Amazon time on returns. Both the customer and the company benefit from proper personalization.
Let the analysts and data scientists in your organization know about the Marketing Analytics & Data Science conference, running concurrently with Content Marketing World. Register today and save $100 with promo code BLOG100.
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Cover photo by Joseph Kalinowski/Content Marketing Institute
Create your very own Auto Publish News/Blog Site and Earn Passive Income in Just 4 Easy Steps
