Home / Understanding the Data Behind Personalization

Understanding the Data Behind Personalization

If you want to increase online conversions and customer loyalty, you have to get a clear handle on your target market: who they are and what they want. And the best way to do that is by collecting the relevant data to personalize the buying experience. Having up-to-date demographic, psychographic, and behavioral data will help you send consumers valuable content, do more effective A/B testing, improve click-through rates, enhance customer service, build trust and loyalty, and boost sales.

The question is, which data is most important? How does your enterprise collect this data, and then how do you leverage it to not only satisfy customer needs, but to exceed their expectations? Here are four types of data you should be collecting, interpreting, and using to personalize your customers' shopping experiences:

1. Demographic Data

It's important to understand that building trust with your customers takes time. At the outset of your business relationship, most customers highly value their privacy, and are likely to be suspicious and unwilling to share personal or sensitive information. But many are willing to share key demographic data, like names, email and mailing addresses, and age and gender, especially if you make it easy for them.

You can gather this data easily through a variety of mediums, including using online forms or integrating a data repository platform or software that runs this process automatically. To maximize completion rates, keep these forms short, with no more than five or six fields. You can also give customers incentives to complete forms, like discounts, rewards, and valuable content in exchange for their information. Over time, you can gather more nuanced demographic data, like income and profession.

2. Psychographic Data

While demographic data will tell you who your customers are, psychographic data will help you understand why they purchase by looking at things like their interests, hobbies, and lifestyles. This information will help you tailor content to customer interests and make product recommendations based on previous purchases, both actions aimed at further increasing sales.

You can gather psychographic data in several ways. Assuming, for example, you've built a higher level of trust based on the marketing you've done using your demographic data, you can simply ask customers for this information. You can also use analytics data from your website to learn what content and product offers have moved consumers in your target market to make purchases. Finally, you can interview current satisfied customers to refine your understanding of their interests and what motivates them to buy.

3. Behavioral and Transactional Data

Perhaps the best way to predict what your customers are likely to buy is to know their search history and what they've bought in the past. You can gather this transactional data based on the selections customers make at the time of checkout, and use them to provide customers with relevant recommendations for future purchases. Refining this practice to a science is what's behind the success of online giants like Amazon.

You also need to collect data on your customers' movements among various marketing channels, like your website, catalog, and brick and mortar store. For example, it's useful to understand if customers' initial interest in a product is generated on your ecommerce site, but that the purchase is made in your store, or vice-versa.

4. Affinity Data

Customer affinities have to do with the ways different products are connected in their thinking. For example, customers who show an explicit interest in lawn mowers might also be interested in hedge trimmers or grass seed. The knowledge gained from affinity data can personalize the buying experience by giving customers more relevant content and product recommendations that give context to their shopping experiences.

An Integrated Approach

Gathering all of this different data can be a challenge, and then pulling it all together to make it actionable is even more difficult. However, to personalize effectively, it’s crucial to take look at your customer from each of these angles, and target them accordingly. Fortunately, there are a number of different tools, systems, and software solutions you can employ to make the process not only easier but more effective. Integrating a data repository that collects, sorts, and provides insights gathered from a myriad of different customer data is a great place to start. With tools like this, busy marketers can fast track their data collection efforts and create a more personalized buying experience to enhance customer satisfaction and boost online sales.

Add new comment

Plain text

  • No HTML tags allowed.
  • Web page addresses and e-mail addresses turn into links automatically.
  • Lines and paragraphs break automatically.

Filtered HTML

  • Use [acphone_sales], [acphone_sales_text], [acphone_support], [acphone_international], [acphone_devcloud], [acphone_extra1] and [acphone_extra2] as placeholders for Acquia phone numbers. Add class "acquia-phones-link" to wrapper element to make number a link.
  • To post pieces of code, surround them with <code>...</code> tags. For PHP code, you can use <?php ... ?>, which will also colour it based on syntax.
  • Web page addresses and e-mail addresses turn into links automatically.
  • Allowed HTML tags: <a> <em> <strong> <cite> <blockquote> <code> <ul> <ol> <li> <h4> <h5> <h2> <img>
  • Lines and paragraphs break automatically.
By submitting this form, you accept the Mollom privacy policy.