Customer data is the most valuable asset in your company. Your sales, marketing, and service teams all rely on the insights you have about your customers to deliver the right experiences at the right time, from lead generation to long-term customer loyalty.
Maintaining an accurate and up-to-date customer database is essential to delivering personalized interactions on a large scale. Without them, your team can’t remember everything they need to know about thousands of leads and customers.
But which customer data do you actually have to collect for each department, how should you store it and how is it used correctly?
Here is our guide to customer data that will walk you through everything you need to know.
Customer data for different departments
Customer data for marketing
Everything starts in marketing for your customer data. You create content and lead magnets that draw attention to your brand, use forms and other lead generation tools – like live chat – to convert those visitors into contacts, and cultivate those contacts to (hopefully) sell-ready leads to become. Here is the customer data you should be collecting for your marketing team
1. Name, email, company name
Marketing is usually the department that brings in the highest percentage of new leads, which means there is pressure to make this information valuable for the rest of the customer lifecycle.
This starts with basic contact information, which should be neatly organized in your CRM and synced in two ways with other major apps like your email marketing platform. This keeps all customer information up-to-date everywhere, so everyone in every department can access the latest information.
2. Website engagement
In the early stages of a new lead contacting your business, it’s important to make sure your website analytics allow you to understand how they are interacting with your business and how best to deliver the experiences you want.
For example, if you are an ecommerce business owner, website activity can help you recommend other similar products that anyone might like via email or retargeting ads on social media.
3. Segmentation data
Information that enables you to divide a contact into the correct groups and lists is one of the most valuable types of data to collect early on. This can include data such as team size, industry and role.
This data not only enables personalized messaging and automation, but also helps you calculate the lead score.
4. Subscription Settings
On the very first form a lead fills out on your website, make sure there is a clear check box so they can sign up for marketing communications. This is an integral part of the privacy policy, but it also allows you to send out the most relevant content by offering a range of options to subscribe to.
5. Lead scoring
Lead qualification data like lead scoring is one of the most powerful ways marketers can help their sales colleagues. With automated lead scoring, points are awarded for positive interactions and behaviors and deducted for negative indicators. It’s the fastest way to instantly gauge the likelihood of a potential customer buying your product, and ideally starts as soon as a visitor is converted into a lead.
Examples of lead score boosters:
- High engagement, like webinar registrations and content downloads
- Long dwell time on your website
- Visiting high-quality pages such as price pages, demo pages, and function pages
- Identification as a decision maker
- High quality market or industry
- Sufficient budget
- Team size fits personas
- Annual turnover corresponds to personas
Examples of lead score deductions:
- Very little engagement with website pages
- Not the decision maker
- Market or industry that is difficult for you to serve
- Insufficient budget
- Team size does not match personas
- Annual sales do not match personas
Customer data for sales
Sales reps create and strengthen the bridge for interested leads to become satisfied customers, and lead each prospect to the right product or service. Whether your team is using an account-based approach to high value deals or a more automated strategy that is effective on a large scale, customer data is vital.
Here is the data that is most important to your sales team.
1. Deal information
Make sure you have a clear record of all related information as soon as possible for every deal you close. This includes data such as invoice amount and frequency, which you can easily synchronize from your CRM with your accounting app. It also helps to ensure that you have an easily accessible copy of the latest version of the contract in your CRM.
2. Customer Lifetime Value (LTV)
Calculating a customer’s lifetime value is a really useful metric for predicting long-term sales. You can measure this by multiplying purchase value by purchase frequency over your average customer lifetime. With a CRM that has calculation properties, you can automatically update them for your active customers.
3. Information about decision makers
Your sales reps get an unmatched view of how each customer’s business works. This also includes who is involved in the decision-making process.
Since the same group of people will likely be involved in future onboarding sessions and upgrade discussions, make sure you save relevant information in your CRM. This will avoid the uncomfortable scenario of them remembering you while you fearfully looking at an empty contact record or passing the deal on to a colleague who has even less background information.
4. Granular, verified segmentation data
When a sales team gets to know a prospect better, this is a great opportunity to review their contact record. Check that industry, company size, and other key metrics are correct, and instantly sync this data with other apps such as email marketing and automation tools that use segmentation.
5. Closed recovered and closed lost data
One of the most important metrics for salespeople is why they are closing a deal or not. Request standardized answers that you save in your CRM and use them to optimize your product, messaging, targeting and sales process.
Customer data for customer service
The collection of customer data is not complete when a deal is closed. Throughout a customer’s time in your company, you can tweak and update their contact record to get the most accurate picture of how your company can best serve them. Here is the best customer data to collect for your service team
1. Customer satisfaction metrics
Metrics like NPS (Net Promoter Score) and CSAT (Customer Satisfaction Score) are incredibly useful for any business in reducing churn and optimizing the customer experience with a stronger product, strategy, and team. These metrics give you an overview of how a customer thinks of your business at any given point in time, and with repeated surveys at set intervals, you can monitor how that sentiment is changing.
Many key figures on customer satisfaction can be recorded extremely quickly. As one of the most popular examples, NPS simply asks, “On a scale from zero to ten, how likely is it that you would recommend our company to a friend or colleague?”
2. Support ticket data
An insightful way to measure both individual and overall customer satisfaction is through your support ticket data. This includes general metrics like ticket volume, topic, and time to resolution, but it’s also worth automating data properties for each customer record, such as:
- Last ticket submitted
- Number of tickets submitted
With automation in your service team, you can create instant triggers that notify your team when satisfaction scores drop below a certain threshold or a certain number of tickets are submitted within a certain time period. Your team can then contact you to review how the customer is doing and to reduce the likelihood of churn.
3. Risk of churn
By combining metrics like customer satisfaction and support ticket data, you can create a bespoke formula for calculating churn risk. With a calculation property in your CRM, you can then measure this automatically and keep an up-to-date and intelligent view of customers with the highest risk of churn.
4. Reason for customer churn
It’s unfortunate, but it happens: you can’t keep every customer forever. If a customer does have to say goodbye, try to understand and record in your CRM what is behind it. Keep these answers standardized (for example, “too expensive” or “problem with the product”) so that you can easily generate actionable reports instead of digging through unstructured data.
5. Reason for customer satisfaction
On the other hand, if a customer loves your business, find out why! Create a standardized set of satisfaction reasons to challenge your customers with high NPS scores.
Collecting, managing, and using customer data is a task you are never finished with. But if you have relevant, accurate and up-to-date customer data, make everything else easier and more effective for sales, marketing, service, and beyond.
In order to get the highest data quality in every app and to enable your departments to work seamlessly together on insights, the bidirectional synchronization of contact data between your apps is essential. Bring your apps together from your CRM to your email marketing software and support platform for the smoothest data-driven operation in your company.
