There are three key touchpoints in a customer’s journey: sales, support and success. The two founding components of any organization selling a product or service are sales and support. The sales team is responsible for finding the customers who would benefit from the product or service they’re selling, and communicate the value to these customers in a way that is relevant to their individual needs. 

The second component, after the sales team has converted a customer, is support. The customer support team is responsible for troubleshooting customer inquiries and assisting them with one-off projects and roadblocks that may come up while using the product or service. ‍

Between the sales and support functions is an important component of the customer journey: customer success. The function of the customer success team is to keep a close eye on your customers’ interactions with the product or service and proactively guide them to a more valuable experience, as shown in the image below. 

Why customer success matters

Data plays a crucial role in customer success. Bringing customer data together allows teams to analyze and draw insights to keep customers happy, help upsell product features and reduce the risk of churn.

Acquisition vs. retention
Since the beginning of time (or the beginning of sales), many companies have held a strong focus on customer acquisition, mainly led by the sales team. Customer acquisition is the process of gaining new customers. It requires organizations to clearly convey the value of its product to its target audience and differentiate its product or service against competitors.

Customer retention, on the other hand, is a metric that measures the ability for an organization to keep its customers over time. While the process of gaining new customers is important, maintaining them and transitioning them into recurring customers is just as critical to the long term success of a business.  

Acting vs. reacting
The key distinction between the customer support team and the customer success team is that the former is a reactive function whereas the latter is a proactive function. The customer support team responds to incoming help tickets. By design, the support function relies on the customer to initiate the interaction and set expectations for the outcomes they desire. 

Adversely, the customer success team monitors customer activity and proactively engages the customer in conversations that enhance the value the customer is receiving and prevent potential grievances. For example, customer success professionals can monitor product usage  and make recommendations on ways to derive more value or reduce cost. Especially in the wake of COVID-19, customers are more price conscious than ever before, and looking out for their bottom line builds trust.

Customers receiving a high value from a product or service are more likely to:

• Adopt new product features
  
• Repurchase at contract renewal 
  
• Recommend the product or service to other professionals 

Hear from Sebastian Joll, revenue operations leader, and William Tsu, customer success operations, at digital lending platform Blend, on their holistic approach to boosting customer success by understanding the sales, deployment and product usage lifecycles. ‍

Best practices‍

Customer data should be at the heart of customer success. Customer success professionals are constantly analyzing their customers’ behaviors and learning from them as they grow. Three best practices should be followed when implementing an impactful customer success approach:

1. Be selective and targeted
‍Product teams are always working to enhance the power of their product and find new ways to add value for their customers while opening new channels for revenue growth for their organization. But research shows that 80% of product features are rarely or never used. While new product features do enhance the user experience, a limitation to new feature launches is feature fatigue: The fact of the matter is that customers don’t have the time or the energy to learn about every new feature you launch and how to use it. 

A great way to see a healthy adoption and retention rate on a new product feature is to target less customers, but target the right customers. The best way to do this is with data. Customer success professionals should always analyze the data, learn from those insights, and apply those learnings to identify new opportunities that will increase their customers’ perceived value. 

While product marketers aim to educate as many customers as possible about the entire product offering, customer success should take a more focused approach. In other words, think of marketing as a ‘mile wide, inch deep’ landscape whereas customer success should be an ‘inch wide, mile deep’ approach. 

2. Connecting the data connects the whole organization
Having a complete view of your customers is vital to taking a true data-driven approach to customer success. The more complete and accurate your data is, the more you can learn from your customers. Customer data should always be shared across teams and departments, of course, with the right guardrails in place. Multiple areas of the business have a hand in the customer journey, and it’s important to avoid data silos and centralize this data in one destination, one source of truth for the entire organization. This way, every team that touches the customer has access to the same customer context.

With all customer data centralized, the next step is to let your customers teach you! Keep an eye out for fast growing organizations accomplishing big business goals using your product, and engage with them to learn more about their journey. From these learnings, customer success professionals can identify similar accounts that could benefit from taking the same approach. Customers appreciate real, tangible evidence that provides easy to understand instructions they can implement to achieve a validated business outcome. 

3. Put the customer first
Strong customer relationships are like any other relationship. You need to invest time to build and nurture them over time. In fact, 86% of buyers are willing to pay more for a great customer experience. 

Customer enablement is two fold: part one is spent researching and preparing for one-on-one time with your account, and part two is spent actually enabling your customer. Before sitting down with your customer, it’s important to anticipate their needs and come prepared with all the information and materials you’ll need to answer any questions they may have. 

Analysis takes place outside of direct customer interaction but is equally important. By segmenting customer data by location, industry, and/or revenue, customer success teams can learn valuable information about how their customers are using their product and the triggers that might predict similar behaviors with other accounts. 

Automation is vital to proficient customer analysis. Time outside of customer enablement should be spent solely on data-rich analysis, not on piecing together customer data and running one-off queries in spreadsheets. With a data-rich, centralized customer dashboard, customer success teams can identify accounts likely to churn and proactively engage with these accounts to alleviate their concerns. They can also identify accounts where there might be an expansion opportunity and suggest helpful products and features for upsell. 

Customer success metrics you should track

‍In order to effectively anticipate your customers’ needs, you need a complete, automated, visual of your customers alongside every interaction with your product or service. An effective method of accomplishing this is to build a customer success dashboard.

An impactful dashboard encompasses each area of your business or product that comes in contact with your customers. (Hint: this is much more than what lives in your CRM!) Depending on your org, your customer data could exist in the following areas:

• Customer engagement
  
• CRM
  
• Support Tickets
  
• Surveys
  
• eCommerce
  
• Product
  
• Financial 
  
• Contract terms
  

Voice of the customer
The first, and quite obvious, place to look for information on what your customers think of your product or service is your customer feedback. Depending on your organization, this could be in the form of in-platform pop-ups, resource and documentation ratings, or, of course, direct customer survey responses. 

Customer support
The best place to look for information on your customers’ pain points specific to using your product is your customer support data. Product developers look for trends in support ticket topics to identify areas where the product or its resources can be improved. 

Typical metrics you’d find on this dashboard include: 

• Customer health score (CHS)
  
• Net promoter score (NPS)
  
• Customer satisfaction (CSAT)
  
• Churn rate
  
• Retention rate
  

Elevated metrics for success 
You can also take your customer insights to the next level with more sophisticated metrics.

• ‍Categorizing customer churn: Keeping records of the specific reasons for churn provides valuable context that can be used to identify churn risks in other accounts, and reduce churn through proactive customer coaching. 
• ‍Forecasted retention: Much like forecasting customer churn, Customer Success teams should have an idea of their projected retention and the revenue impact from these renewals, to be shared with finance. ‍
• Ideal customer fit: Track expansion deals by customer fit to better categorize churn and expansion motivations. It’s possible that the customer targeting strategy can be optimized to better select qualified customers to enter the sales funnel. ‍
• Advocacy: The most valuable customers are those who are willing to promote their experience with your product or service. Measure your percentage of customer advocates against the rest of your customer base, and track the status of committed customer advocacy programs (such as case studies, sales references, and speaking engagements) to gauge the value of these relationships. 
  

Watch the full story of how digital lending platform Blend automates its data integration to deliver business-wide data analysis and drive bottom-line growth.