If your business has customers, you have customer data. And your customer data is the key to fuel anything from sales and marketing, to improving your customer experience.
Customer data is basically any information that your business collects about its customers — anything from contact info, to demographics, to how your customers use or interact with your product.
This data is incredibly valuable to your business, and you should be collecting and analyzing it if you want to offer products and services that meet the needs of the people you're trying to serve.
Even though more customer data is being generated and collected than ever before, only 6% of enterprises believe they have complete visibility across their customers' experiences. So, while most businesses don’t lack the data, most of them still aren't prioritizing harnessing it for their CX strategy, either.
When most teams are creating a CX or customer support strategy, the first things they think about are:
- Tone and style guides
- Escalation paths
- Hiring forecasting
- Team structure
- Tagging systems
- Channel options
While all these are important, they overlook the aspect that can help teams get the farthest: incorporating customer data into their buildout. All the above bullets will undoubtedly help create a stable strategy, but performance will quickly drop without the essential backbone of good data.
It's not typically until a bit later in a team's maturation that data comes to the front of mind. Often it's when teams are trying to demonstrate their efficacy or create better metrics around performance that they start to think critically about data. However, if you build and prioritize data right from the start, before you might think you need it, you give your team a more solid foundation to work from.
What does adding data to your CX strategy look like?
The first step for most businesses is creating a place to unify your data across disparate sources. Creating a single source of referenceable truth allows you to glean critical insights from your data and share it with other teams at the company. Let’s walk through the steps you need to take to integrate data into your strategy.
Create a single source of truth
When you're collecting a wealth of data across multiple channels, it can become difficult to make sense of it all. As a result most of it gets lost, or an incomplete picture is created. Using the right tools to manage and process your customer data is going to help you make sure that information isn't siloed, and that everything is stored centrally so the whole team has access to it.
You can create your single source of truth using any number of technologies. For instance:
- Spreadsheet software, like Airtable or Google Sheets
- Dashboard software, like Domo
- A data warehouse, such as Snowflake
- Something homegrown, built by your engineering or product team
The most crucial aspect of whatever you choose is its ease of management for your team and the ability for your software stack to integrate with it. If it’s too tricky to use or doesn’t have a direct integration, your team might not have the inherent skills to use the new system. That will hamper adoption and, ultimately, your ability to move forward with a data-driven strategy.
Integrate your tech stack
Prioritize using products with robust data functionality that make your information easily accessible. A great way to decide if a product will be a fit is to look at how it treats data democracy, integrations, and APIs. For instance, Fullview's newest direct integration with Intercom is an excellent example of what you should look for—it shows that Fullview intentionally exposes data in other sources and offers robust integrations. Products like that make it easy to hook them directly into your single source of truth.
Use data rather than your gut
Once you have the data at your fingertips, use data-driven decision-making rather than "gut feeling." When assessing if a business decision is right for your team, consider your metrics as your first decision-making point. For example, if you’re considering separating out specific types of conversations to be managed by a separate team, you can estimate the impact of that move, and understand how many members that team will need to have by looking at historic data from your helpdesk, rather than just eyeballing it, and adjusting after the change has been made.
Why prioritize data as the first step in your CX strategy?
With so many other pieces you could prioritize as the first step in your CX strategy, why should data be the first? After all, wouldn't it be more effective if you set up triaging practices or created staffing predictions? When you’re starting out, doesn’t having a fully-fledged data strategy with so few customers to analyze feel silly?
While it can feel like overkill, and there are other projects that may seem easier or more urgent, they won't have the same long-term impact as ensuring that you set up effective data practices from the start. Here are a few reasons why data should be the first thing that you prioritize:
Data is hard to set up retroactively
Once you have gotten your CX strategy up and running and there is some velocity to your team, getting the resources and time necessary to retrofit data into your solution can be challenging. Creating the data framework from the start and iterating as you go makes it easier to unify data slowly rather than the huge lift of getting everything into place retroactively.
For instance, consider the energy it takes to set up a dashboard and integrate products as you add them to your tech stack. Then consider the energy it takes to create a dashboard and add a large backlog of many disparate components all at once. It is much more accessible to start slowly, and add on progressively, then take on the herculean effort of fitting a whole data system in at once.
The latter strategy requires a significant effort for data mapping, integrating disparate tools, and ensuring that the dashboards look the way you want them to. If you spend the upfront effort to customize your dashboard and add new streams of data as they come, it minimizes the required effort in the long run.
Creates a better long-term customer experience
As you grow, you may want to start thinking about multichannel or omnichannel support. Having data pipe into a single source of truth makes it easier to know when to introduce new channels with less concern about how they'll perform — you already know what your customers do or don’t like and have a way to analyze it effectively. It also empowers you to staff up to an efficient level to manage those channels and create a unified experience for your customers as they travel through your product ecosystem.
For instance, if you do not have a data backbone, you might be unable to track customer actions across chat, email, and phone. According to Forbes, "the most important piece [of growing your customer experience strategy] is the unified customer profile that includes all transactional, behavioral, and sensor data into a single ID that goes with the customer wherever they interact with a brand. Brands effectively leverage unified customer profiles are more likely to experience revenue growth, increased profitability, and higher customer lifetime values."
Personalization in the customer experience is key. Using your customer data can help you create a more personal customer support experience at scale.Your data will show you who your customers are, what they like, what they buy, how they use it, and so much more valuable information that can help you tailor your support to their needs. This is also extremely valuable for new products or features. Customer feedback should be a key part of your development cycle.
Provides more breadth to understand the customer experience
Rather than just basing your evaluations on a single metric, setting up your data pipeline from the start lets you correlate and compare multiple metrics to get the best picture.
For instance, in a recent survey from McKinsey, 93% of respondents reported using a survey-based metric as their primary means of measuring their CX performance. Still, only 15% said they were satisfied, and 6% expressed confidence in that metric enabling strategic and tactical decision-making. The ability to compare multiple metrics and paint a more complete picture of what’s really happening, will give you more confidence that the data is telling you something accurate to the real customer experience.
When you set up a more robust data structure, you empower your team to make better tactical and strategic decisions as you grow and give a broader representation of the customer experience.
Facilitates self-service and proactive support
Having data at your fingertips allows you to showcase helpful information to customers before they know they need it. For example, Fullview preemptively gives your team access to console logs that show precisely the issues your customers are running into, whether they know how to access the browser console or not. Information like this gives your support team superpowers to troubleshoot for your customers without needing to ask them for additional information. It feels like magic!
This data also gives you a leg up when creating self-service content and documentation. With data, you can see what issues people care about or are reaching out about most frequently and understand what levers you have to improve the experience. For instance, if most of your volume comes through email, it would be wise to prioritize email-adjacent self-service solutions.
Elevate your CX beyond the bare minimum
While it's great that you're getting your customers timely responses to their inquiries, that is just the bare minimum of what you should be offering. Staffing efficiently means that your team will be able to work on other initiatives outside the inbox that continue to grow the efficacy of your support team. It also preps you against seasonal backlogs or pressure from not being maximally staffed. Beyond just hiring internally, data empowers you to understand if customer service outsourcing or creating differentiated teams within your organization may be a way to free up additional resources for more serious strategic efforts outside the queue.
Having year-over-year data helps you predict where your peaks and valleys are, as well as what your potential baseline for volume is. You'll have a better picture of which channels your customers use most and if there are other channels you don't currently offer that your customers are hungry for.
While it's great to send emails and deliver responses when people expect them, having time to devote to new practices like customer success, proactive support, or CX experiments has a longer-lasting effect on customer loyalty and lifetime value.
Proves the value of CX to external teams
Teams outside of CX don't always find it easy to understand the impact of what customer experience teams do. Often, outsiders can oversimplify it as just "helping the customer."
When you have a robust pool of information that you can also cross-reference with data from outside of your team, it proves the value and efficacy of your work. For example, you could correlate the number of times a customer has reached out to your support team with their expansion rate and determine if people who contact support are more or less likely to purchase. You could do something very similar with metrics like first contact resolution, or time to first response, and a user's intent to buy—e.g., if someone gets a quick response from your support team, does that make them more likely to buy?
This type of data is precious to teams outside of CX. Beyond that, you could use the data mined from customer experience interactions across marketing, product, and even engineering:
- Use data to inform marketing efforts and personas
- Use data to track and measure the impact of bugs
- Use data to prioritize product releases
The information exposed by adding data to your customer experience strategy early, rather than waiting and creating a much larger project later, is well worth the associated start-up costs.
Wrapping things up
Build out your data from the get-go so that, as you grow, you have scalability already built in, rather than having to fight for it retroactively. You can then spend your time on so many more meaningful things, like creating self-service functionality, up-leveling your proactive support, staffing efficiently for the holidays, and even helping your external teams, such as engineering and marketing, boost their functions. It may seem daunting, but trust me that the initial lift is much smaller than a fully-crafted fix in the future—you've got nothing to lose!
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