Anyone who works in marketing operations knows that customer data is a critical foundation for success. But even with this knowledge, most people underestimate just how impactful customer data is at every point in the customer lifecycle.
Customer experience is driven by data and is vital to the success of your business. A report from Dimension Data found that 81% of companies say customer experience is a competitive differentiator. Some 73% of business executives say that delivering a relevant and reliable customer experience is critical to their company’s overall business performance today.
So, it’s clear most people understand that customer experience is important. But businesses still haven’t figured out how to deliver that critical experience. In fact, a recent survey found that only 15% of organizations consider themselves very effective in delivering a relevant and reliable customer experience.
The key to improving the customer experience lies in your customer data. Your ability to collect, integrate, clean, and supplement customer data plays a critical role in the experience of your customers.It dictates, almost completely, how your brand engages with prospects and customers at every stage. Even moderate improvements in data collection can have a big payoff down the line.
In this article, we’re going to examine some of the goals companies have at each stage of the customer lifecycle. We’ll also look at how customer data plays a key role in your ability to effectively engage with customers at that stage.
Customer Lifecycle Stage: Discover
Discovery is the first step in the customer lifecycle. It’s where the prospect starts to gain awareness of your brand and product. It’s critical for companies to make a good first impression at this stage and to engage with prospects appropriately from the very first contact.
At this early juncture, your customer data management practices directly impact your ability to improve customer experiences down the line and throughout the funnel. You have to collect enough data on each prospect to:
- effectively segment and personalize marketing materials
- score leads
- reach the right prospects
Customer data management allows you to effectively collect, use, and enrich the information that you have for each prospect and customer. Then, you can use that information to create a tailor-made experience.
You can speak to their biggest concerns, anticipate their needs, and deliver the content they need, when they need it. This stage may be the most critical time in the customer lifecycle, because it is when first impressions are established, and those impressions are hard to change.
Your company’s effectiveness at these tasks is directly related to your ability to grow your customer base. In fact, data-driven organizations are 23 times more likely to acquire customers and nine times as likely to retain customers.
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Customer Profiling With Segmentation and Personalization
In the first days of the customer journey, your goal should be to collect as much relevant data on prospects as possible and use that data to segment your leads.
Segmentation is the process of categorizing prospects and customers based on data. Where they live, how they have engaged with your company, and what problems they are looking to solve are good examples of how companies segment customers. By grouping them together in such segments, companies can more effectively personalize communications to match the needs of their customers.
The more we know about our prospects, the better we can speak to their most pressing needs through segmentation and personalization. Initially, you’ll probably have little data on hand about new prospects. But with a plan in place to collect more data and enrich customer profiles, you can more reliably improve customer experiences.
Evaluate Prospects with Lead Scoring
Lead scoring is the process of assigning value to the leads in your CRM system. This could be a letter grade—A, B, C, D, or F. The lead’s score could also be conveyed by a numerical value on a scale of 1-10 or 1-100.
Larger companies that service more leads at one time may need more complex systems to determine which prospects marketing and sales teams should focus on.
Lead scoring systems can look at a range of different attributes to assign scores to leads, including:
- Professional information. Some prospects are more buy-ready than others and the information they provide can signal this. Some attributes—like having a non-business email address or not holding a decision-making position—can result in negative lead scoring attributes.
- Demographic information. Who is the prospect? Where do they work? How big is the company? Certain characteristics may be more valuable to your company than others. They may signal larger deals, more engaged customers, or a better fit for your solution.
- Behavioral information. How has the prospect engaged with your brand? This includes data regarding actions on your website, contacts with sales reps, or engagement with your advertisements on other channels. In lead scoring, more engagement with your most valuable content is a sign of a high level of interest, and should trigger increases in their lead score.
Your ability to collect and organize this data is critical for accurate lead scoring and prioritization of your time. Without it, your sales reps will be flying blind.
Reach the Right Prospects with Improved Understanding
To consistently fill your pipeline with high-scoring leads, you need to understand your customers.
Who they are. Where they hang out. What they want. What they need.
When you know those things, you know which channels to target and what messages to deliver. Additionally, improved understanding allows you to leverage look-a-like targeting. This form of targeting uses customer profiles to help businesses get their ads in front of the prospects that are most likely to be interested in their offer.
Customer data doesn’t just allow businesses to engage effectively with prospects—it helps locate them in the first place.
Customer Lifecycle Stage: Explore
In this stage of the customer lifecycle, customers begin to explore available solutions. They might have a list of products that meet their initial needs and are starting to dig into how each solution would actually fit with their current processes.
Customer data couldn’t be more critical in this phase.
It’s during this exploratory stage that customers have their most important questions about your product or solution. You need to answer those questions with timely communication and educational content to endear them to your brand and position your product as the true solution to the problems they are facing. This task is complicated by the fact that you can’t always rely on a prospect to ask the questions that they have. You have to anticipate and predict those questions. And your ability to do that comes down to customer data management.
During this stage, solid customer data helps you improve communication, target different personas through specific channels, and use A/B testing to increase your effectiveness.
Effective communication at this stage is all about education. Your prospects will have questions about your product, brand, and industry. They’ll want to know how your product compares to competitors. They’ll want to know what other companies in a similar position have enjoyed and disliked about your product.
Knowing what is important to a prospect is necessary for effective communication. This knowledge comes from your customer data. For example, if you collect information about which products a prospect is interested in, you can choose the appropriate marketing materials to send them. Knowing other information, such as their job title, may provide more insight into their motivation, and allow you to further personalize your approach for their needs.
Customers expect you to be able to anticipate and deliver what they need, when they need it. Without data, your efforts will struggle to hit the mark.
Hone in On Effective Channels for Specific Personas
It’s critical to differentiate between personas at this stage. A Marketing Manager and Chief Revenue Officer may come to Insycle for the same basic goal—to get help with customer data management—but their reasons for doing so couldn’t be more different.
Customer data allows us to differentiate between them, and craft a personalized approach based on that data. Certain personas are likely to convert better through some channels than others. Using the above example, the marketing manager might be a better candidate to target on Facebook, whereas the chief revenue officer might be more effectively engaged on LinkedIn.
Deeper than channels, customer data allows you to hone in on the right marketing mix for each persona.
A/B Testing Improves Effectiveness Over Time
Customer conversion data is a lever for growth and improved customer experience. When you can effectively track how different touchpoints influence customers’ buying decisions, you can better anticipate their needs throughout the funnel.
A/B testing is the process of comparing different approaches and seeing which convert at a higher rate. For instance, you might test which product image produces more conversions. More deeply, you might A/B test more complex things. For instance, a single page checkout is likely to convert at a higher rate than a multi-page checkout. But you collect more data with the latter. Does the increase in conversions offset the dip in customer lifetime value?
Ultimately, A/B testing impacts every stage of the customer lifecycle but plays its most critical role in the exploratory stage, where a majority of prospects spend the bulk of their time. Their engagement with your brand and content set the stage for closing the sale.
With robust customer data management, companies put themselves in position to run better split testing experiments and better align the customer experience with their needs.
Customer Lifecycle Stage: Buy
Once buyers have discovered your company and learned about your product and competitors, they are ready to make a decision.
In this stage, conversion data plays a critical role. While engagements with content throughout the customer lifecycle are critical (and conversions should be credited through effective attribution), engagements during the buying stage often have a direct impact on when consumers pull the trigger.
Let’s take a look at some of the ways that customer data management can help companies engage with prospects in this stage.
A better understanding of prospects and customers, enabled by customer data, makes it easier for companies to forecast success rates throughout their pipeline. Effective lead scoring is a key element here.
Accurate forecasts assist marketing and sales teams with budget allotments and help them prioritize initiatives with data-backed decision-making. This makes your organization more agile.
Improve Cross-Sell and Upsell Effectiveness
Collecting more customer data gives you unique insight into your customers’ needs, concerns, and desires. You may have additional offerings that extend the functionality of your product or align with their needs in other ways.
But without customer data, you have no way to discern what additional products your customers are truly interested in. That applies both at the point of sale and in the weeks and months afterward.
If you are a SaaS company, collecting data about how people use your product can provide a lot of insight into what additional features might be useful to specific customers. Pushing them toward higher-dollar plans with features that address their specific concerns can be a reliable and critical lever for growth.
Connect Them With Pain Point-Specific Content
In the buying stage, a prospect usually needs to see certain types of content before choosing your product. This content needs to answer very specific questions that the prospect may have when making their buying decision.
For instance, a chief marketing officer (CMO) might need to know whether your solution includes audit logs with information about changes—who made them, when they were made, and what those changes were. On the other hand, lower-level marketing managers would be more concerned with the base-level functionality of the software.
If you are catering to both personas, it’s important that you are creating content that speaks to the specific needs and pain points of each persona. Sending a CMO content that is catered to marketing managers is likely to miss the mark—and push them away from your brand because they don’t feel understood.
Customer Lifecycle Stage: Use
Once prospects have purchased your product, they move into a new bucket—the “users” bucket.
They are now customers of your business. But your reliance on data to provide a better overall customer experience shouldn’t stop once they hit the “buy now” button.
Once a prospect becomes a customer, your focus must shift toward customer success. Customer data is, of course, a critical component in this effort.
You should leverage your current customer and user data to:
- reduce churn
- improve customer persona understanding
- inform data-backed decisions
Let’s take a look at how data specifically helps companies with users that have purchased their product.
Reduce Churn Through Improved Understanding
There is an argument to be made that reducing churn is the most effective approach to growth for early stage companies.
Ultimately, it comes down to customer experience again.
A customer who is having a good experience with your product and brand will be less likely to churn. Above all else, they have to find your solution valuable. Does it help them to solve their problems? Do the end results align with the promises that were made to them, explicitly or implicitly, throughout the sales process?
User data is often more critical than actually listening to what customers have to say. What we mean by that, is that customers often come into a sales process with many concerns that, once answered, don’t have a big effect on how they interact with your product.
On the other hand, the user data tells you what your customers actually find valuable about your solution. It provides you with the information that you need to know to identify compelling upsells and cross-sells to offer to each customer. It shows you how customers could better use your product to meet their goals. Then, you can use that data to influence product roadmaps and guide users toward the corners of your solution that they may be missing out on.
User Data Drives Data-Backed Decisions
Your customer and user data doesn’t just help you reduce churn. This vital data is useful throughout the customer lifecycle.
Your user data is likely to surprise you. Features that you thought might be a secondary consideration may end up being some of your users’ most beloved functions. Data can open your eyes to a host of new use cases that could be harnessed to improve content and engagement at all stages of the customer lifecycle.
User data provides clear insight into what is important to your customers, even if they struggle to vocalize those needs throughout the sales process.
Customer Lifecycle Stage: Ask
When customers have stayed with your company for a while, their opinions become valuable resources. If they have been happy enough with their experience to stick with your brand, you need to make it your mission to understand why.
Customer opinion analysis is something that too few companies prioritize. Speaking with your most loyal customers—the ones that are most familiar with your brand—can provide unique insights.
These customers have a true bird’s eye view of your customer experience. They’ve been through every step in the process and can provide quality feedback.
Getting the right feedback requires that you ask the right questions. Customer surveys and conversations are part of the data collection process. But, the data that you have already collected should be used to design the questions that you ask. Customer data lets you hone in on what those questions might be.
Say, for instance, that your customer data showed one of your largest customers wasn’t using one of the main feature sets of your solution. You would want to find out why. With user data, you can pinpoint why organizations find specific portions of your solution useful while shying away from others.
Customer Lifecycle Stage: Engage
The customer experience doesn’t end once a prospect becomes a loyal customer, either. You have to continue to engage with them to deepen that relationship and improve upon their experience.
In this stage of the customer lifecycle, critical customer data can be used in many ways. Here are some of the things you can do with it:
- Improve personalization. You’ll need to continually deliver new content to your customers. Over time, as you collect more data, you can use that data to speak more directly to the concerns of each customer.
- Optimize lifetime customer value. Use customer data to see exactly how strategy changes affect the lifetime value of each customer. Use customer data to create lifetime value models.
- Optimize loyalty programs. Loyalty programs are in themselves marketing channels that must be monitored, optimized, and analyzed for success.
Customer data will play a critical role in the way that you engage with customers for their entire stay with your brand.
The Customer Experience is Forever
The customer journey never ends. Customer data can and should be used throughout that journey. You can use it to improve your understanding of customers and better address their concerns at each stage. Customer data also enables you to improve personalization and create automated campaigns that feel more like conversations and less like marketing initiatives.
Insycle analyzes customer data in CRMs for the most common data problems, pinpointing poorly formatted records, duplicate data, low-quality data, and other issues. With Insycle, operations teams can fix CRM data issues with just a few clicks and automate the data maintenance process to improve the results of marketing initiatives. Without Insycle, bad data costs are a major blind spot and roadblock for execution for marketing and sales leaders.
Want to improve customer experiences? Learn more about Insycle's advanced CRM data cleaning and enable your teams to focus on big-picture activities, while removing redundant data maintenance processes from their plate.