Which 15 Customer Data Points Are Most Important?

With demand for customer analytics on the rise (more than doubling between 2020 and 2025), it is essential to capture the correct customer data points to inform customer intelligence and performance evaluation.

In fact, modern businesses and contact centres rely on customer intelligence in a big way. These data points reflect the 360-degree picture of the customer. They reveal true intent and opportunities for engagement and sales. Combined with predictive analytics, they can help you anticipate problems on the customer journey and prepare for a speedy resolution. It’s no surprise, therefore, that customer analytics will be a $24+ billion market by 2025, up from just $10.5 billion in 2020.

Here are the 15 most important data points to measure as part of your customer analytics strategy:

1. Full name – An essential data point, the customer’s name helps you personalise communication, tag omni-channel interactions, and track the journey across different mediums
2. Location – This includes the primary location of residence/product usage, as well as frequently visited locations, favourite sites, and the overall region of operations
3. Intent – This slightly complex data point reflects the real driver of interest – e.g., when a teetotaller purchases a bottle of wine as a gift on Mother’s Day
4. Industry – Like intent in the B2C space, the industry and company size of B2B consumers tell you about their purchasing patterns, needs, and decision-making level
5. Email open times – Every customer will have their preferred time of day for email engagement, making it a crucial data point to measure if you want to achieve a high Click-Through Rate (CTR)
6. Attribution – Attribution data captures the route that led to the customer or prospect to your website, helping you fine-tune marketing investments
7. Email history – Keeping track of email data can help you contextualise telephonic interactions and provide a more seamless CX
8. Lifetime value – Customer lifetime value (CLV) tells you the measurable value of business a person will generate throughout their lifetime, either personally or via referrals
9. Contribution – Similar to CLV in B2C, contribution captures the total profitability a B2B customer brings to a product or service company’s annual revenues
10. Persona score – This increasingly popular data point tells you how closely a customer resembles their assigned profile or persona, and the possible magnitude of deviation
11. Deal velocity – For high-value purchases (or even upselling/cross-selling campaigns), deal velocity data indicates how fast a customer can be persuaded to close a deal
12. Life events – This data can be extracted from publicly available social media information, helping to align the product journey with a customer’s ongoing life experiences
13. Real-time interaction data – The quality of customer interactions in real-time (both call and email) can help pre-empt disputes arising from poor service quality
14. Top keywords – This data encapsulates the keywords that are most frequently searched by the customer, acting as a window into their intent and aspirations
15. Time of calling – The average time slot for making service calls can help you predict peak periods for your contact centre and staff accordingly