At a time when artificial intelligence is redefining customer relations, first-party data (collected directly from your audience) is taking on a whole new dimension. It is no longer just a line in your CRM, but the essential fuel for powering the latest AI tools.

By collecting your own data, you enable your conversational agents and chatbots to offer ultra-personalized and seamless interactions. Even better, this proprietary data is the key to “Fine-Tuning“: it allows you to adjust generative AI models so they adopt your specific brand voice and respond precisely to your customers’ unique needs, whereas general models would only scratch the surface.

Understanding your customers and their LTV (Lifetime Value), both broadly (by creating buyer personas) and on a more individualized, contextual level—is crucial for boosting performance at every stage of the conversion funnel.

Conversely, a lack of audience data can lead to poor decision-making, missing out on new business opportunities, and losing market share to better-informed competitors.

In this article, we focus on the primary reasons why a company should collect data and how to activate it based on the specific results they aim to achieve.

<a href="https://www.adictiz.com/en/blog/why-collect-data/
” style=”color: #000000; text-decoration: underline;”>Data collection involves gathering, structuring, and utilizing information from various sources for the purpose of analysis or decision-making. This process involves systematically collecting and organizing data points, which can take the form of numbers, text, images, and more.

There are three main types of data:

• Zero-party data or first-party data are obtained directly from consumers. The former are shared directly by users (via a form, for example), while the latter are derived from their behavior on a website. They are considered more reliable (since they come directly from the buyers), especially for analyzing the needs and expectations of prospects.
• Second-party data: gathered by trusted partners and shared or sold as part of a collaboration;
• Third-party data, obtained from external sources with no direct relationship to the potential customer or the company. They must therefore be used with caution due to the difficulty of assessing their reliability and potential GDPR & Privacy-first compliance issues.

Now that we are familiar with the different types of data, let’s move on to the right reasons to collect them!

1. Make better business decisions

Data is, first and foremost, information about consumers. The better a company knows its audience, the more it will be able to make the right decisions and avoid wasting its resources.

In addition to collecting relevant data on its customers, a company can use it to segment its clientele. This allows it to create different groups of prospects based on their purchasing behavior or preferences.

These customer segments will then help the company personalize its acquisition or retention strategies by tailoring its message to each group or by delivering it through the channel they are most likely to use.

2. Evaluate and boost customer loyalty

Retention has become just as important an issue, if not more so, than acquiring new customers. The data a company holds on its users will, in effect, allow it to identify purchasing behaviors and target them with more relevant offers based on their previous orders.

A loyalty program is an excellent way to collect data for this purpose. The brand will be able to track and reward purchases and other interactions made by its customers. This will increase their Lifetime Value and, consequently, the revenue generated from its most loyal customers.

3. Analyze and predict customer behavior using first-party data

First-party data (or behavioral data) represents all the information a company collects regarding how a customer interacts with its brand. This refers to the pages they visit on the website, the resources they have downloaded from the blog, or even the email campaigns they have opened over the past few months.

Performing an analysis of customer behavior is becoming increasingly important due to consumers’ ever-growing expectations for unique and personalized content. Interactive marketing is an excellent lever for collecting even more granular data on buyer behavior and offering tailored marketing content and commercial deals.

4. Improving your offering through customer feedback

Much easier to collect than feedback from a user test, customer reviews are a goldmine of information on how customers use a product or service. In addition to being a powerful reassurance lever for prospects, customer reviews bring to light ideas for improvements or new features that will make the company’s offering more relevant.

Co-creation strategies, through surveys or idea-sharing and customer feedback forms, …are extremely useful for collecting and activating customer data. They make it possible to establish an interactive relationship, target specific pain points, and optimize the offering with ultra-high efficiency.

The brand Cyrillus thus shared its data collection form via a personalized landing page. The latter enabled it to facilitate the enrichment of its CRM with missing and valuable information (first names + phone numbers). This allowed the brand to requalify its database to better reach and convert its target audience.

5. Optimizing your marketing strategy by collecting customer data

As we’ve seen, customer data makes it possible to build a more accurate profile of the target audience. The company can then adapt its marketing strategy accordingly, for example, by identifying more effective rewards or prizes to boost participation rates in its contests.

6. Streamlining prospect targeting and customer retargeting

The data collected at every stage of the customer relationship provides valuable information to better target prospects and retarget former customers. A visitor who has viewed a product page on the company’s website can thus be retargeted on another platform with an ad corresponding to the item in question or to similar products.

7. Enhancing the customer experience

Companies that analyze their prospects’ behavioral data will also be able to better understand their users’ buying journey. This is an extremely effective way to pinpoint potential barriers to purchase. The company can then remove them by minimizing friction or by providing relevant information (on pricing, delivery details) at the right moment.

8. Reducing lost business opportunities

Transactional or behavioral data are also excellent levers for maximizing customer lifetime value (LTV). In general, collecting and deeply analyzing customer data allows you to allocate your resources where they are most needed. More concretely, this data can power product recommendation algorithms at every stage of the buying journey. As a result, they are valuable tools for boosting upselling and cross-selling, thereby increasing the average basket value for every consumer.

9. Collecting data to drive innovation

Customer data represents an invaluable opportunity for innovation by building on a detailed analysis of consumer trends. Not only do they fuel product innovation (through co-creation, for example), but they also facilitate marketing innovation (exploring new formats and communication channels).

10. Automating interactions between the brand and its customers