Customer data is the information a business collects about a user while they interact with their product or platform, it tells you who your customers are and how they are using your service.
There is a wide variety of user data that a business should collect. We’ll get to that in a second. But first, the question is: why is it important to know all you can about your customers?
In essence, if you want to run a successful business, you have to know everything you can about your customers. Every area of your business relies on it:
- Knowing your clients’ pain points or needs is the foundation of a successful business. We’ve all seen those horror stories of companies who don’t understand their customers, rush to gain VC funding, and build a product that nobody wants!
- Understanding your users’ terminology and ‘speaking their language’ enables your Sales team to build better rapport with your customers. And for your CS team, they will be able to better instruct clients on which features of your product are most relevant for their use-cases.
- Analysing your customers’ feedback or spotting trends in their platform usage informs your Product team on which features to add to the roadmap.
- Knowing your customers’ industry trends helps your Marketing team craft content that will be valuable to your users. If you understand what publications your target audience read or keep on top of the latest industry news, you can build a Webinar series to add to the conversation. Or send highly targeted and personalised marketing campaigns that are timely to these topics.
- Analysing your customers’ ongoing engagement with your platform informs your product-market fit and instructs your business on which future direction to take.
Types of Customer Data
Now that we’ve covered the importance of customer data, what are the main categories?
Personal data splits into two overarching categories: personally Identifiable Information (PII) and Non-Personally Identifiable Information (Non-PII).
PII relates to anything which can be used to identify an individual. This includes their name, email address and physical address. Similarly, data from more general sources, such as company, location, and age can be linked together to identify an individual.
With GoSquared, our auto-enrichment will link a contact’s social media information to their profile. Usually, this will be their LinkedIn profile. This gives you and your Sales team all the information they need to engage with your customers in a personal way. In addition, these profiles can also be used to segment users into their relevant groups to send out highly targeted marketing messages at scale.
Non-PII is anonymous data. For example, a users’ IP address or device IDs.
For GoSquared, these are counted as anonymous visitors and can still be tracked on your Analytics dashboards.
Behavioural data reveals how your users interact with your platform. Over time, you can use this to demonstrate trends in behaviour and inform changes to your product.
Examples of behavioural data include which features users activate, how much time the user spends on your platform, average order value, and heat maps.
Behavioural data will answer key questions about your product; which areas customers find value in, which areas they struggle with, and where you should make future improvements.
With GoSquared, you can track any custom behavioural events across your entire user-base. Then use the data to build your Smart Groups and trigger marketing or customer success campaigns.
For example, you could track customers who show minimal engagement with your platform and create a ‘Churn Risk’ Smart Group for your CS team to reach out to. Or, identify users who have activated all of your key features, create a Smart Group of ‘Super Users’ and reach out to them for a testimonial.
Engagement data has a similar flavour to behavioural data, but while the latter focuses more on in-product activity, engagement data typically refers more to marketing activity.
Behavioural data will analyse what actions users make once inside your platform; engagement will look at how they get to your platform in the first place. For example, which marketing channels drove them to your landing page? How did they interact with the landing page once they got there?
Engagement data is vital to optimising your marketing campaigns. For example, track your email open and click-through rates with GoSquared Automations. Use this to A/B test different subject lines or different discount offers.
From your dashboard in GoSquared, you can also track exactly which marketing campaigns have driven the most traffic to your landing pages. So don’t spend a penny more on low-value campaigns, and start doubling down on your winning ads.
Once they arrive on your site, you can also track user journeys to discover which pages see the highest engagement (a great indicator for where to place a Prompt!)
Finally, attitudinal data informs you on how your customers feel or talk about your brand. Typically, unless users write up online reviews of their own accord, you will need to proactively reach out to customers to gather this data.
Sending ‘Net Promoter Score’ surveys to clients is one of the most popular choices for this purpose. Ideally, you would deploy a survey in-app when a user is actively using your product. You can ask them to rate your product on a scale of 1-10 and offer the opportunity to give feedback. This is a great way to find out what customers are most happy about and what product areas they are most disappointed in.
You can use high scoring surveys to request testimonials. Low score surveys are a lagging indicator of churn. CS teams need to follow up on these immediately and take feedback to Product Teams to investigate future improvements.
Although it might sound a bit old-school in this day and age, sitting down in your customers’ offices for focus sessions can be one of the best ways of getting detailed & honest feedback. In a world where we increasingly communicate online, spending time with a customer offline can often be the best way to truly understand how they feel about your brand and product.
So, what’s next for my customer data?
In this article, we took a look at the importance of customer data and the four main categories of data you need to know about. Analysing user data and making informed product or marketing decisions based on that data is the foundation of any successful business.
Keep an eye out for part 2, where we will take a look at managing your customer data and avoiding some of the common pitfalls in collecting and managing user information 🙌.