How CRM Customer Intelligence Increases Conversions and Accelerates Revenues
- Research shows that 82% of the Best-in-Class sales organizations use four customer intelligence methods to systemically grow revenues
- The research also shows that companies that develop and refine these methods achieve higher campaign conversions, sales win rates and customer retention
- The data finds that companies in the most competitive industries had a disproportionately higher use and benefit from customer or consumer intelligence
From more than three decades of sales coaching, I've found that most sales and marketing executives believe they know what their customers most want when making purchase decisions. And most executives are partially correct.
Unfortunately, their inaccuracy in really knowing what customers most want, how they measure value and how they make purchase decisions increases sales cycle durations and decreases sales win rates. In the legendary words of Mark Twain, "What gets us into trouble is not what we don't know. It's what we know for sure that just ain't so."
Customers are not homogeneous. It's a serious mistake to presume what your customers most want or assume buyers all want the same thing. Customer intelligence is the prevention to this selling mistake. It's the process of gathering and categorizing customer data and applying that information to deliver personalized communication, produce the most relevant offers and proposals, improve sales conversions and grow customer relationships.
There are four primary intelligence methods or disciplines. Each delivers different capabilities and benefits. Research performed for the Sales Excellence Report shows that they are not mutually exclusive as 82% of the Best-in-Class sales organizations use a mix of each method.
Here are the four methods.
Ideal Customer Profile
The ideal customer profile (ICP) is a description of the customer organization that will most benefit from your product or service. These high fit customers realize the fastest sales cycles, highest close rates, longest customer retention and highest Customer Lifetime Value (CLV). They are your best advocates and deliver the most referrals. They are your most valuable customers.
There are no fixed criteria for ICP, but common criteria include industry, company size and geography.
Some industries, such as the technology sector, will include things like technographics (what technology companies use). Other factors may include environmental or behavioral characteristics, such as how a customer uses your product.
While other types of account intelligence such as customer insights will focus on people, the ICP is applied to the company.
The ICP will heavily influence downstream marketing and sales strategies, go-to-market plans, investment allocation and a host of processes such as campaign targeting and lead scoring.
Customer segments are account groupings based on shared attributes.
Customers can be manually or automatically mapped into dynamic account segments and used for marketing, sales or customer service purposes.
For example, customer segments can be used to allocate investment pursuant to customer margin, profit, CLV or other contribution. A company may choose to deliver high touch customer support with Service Level Agreements or entitlements for high contribution customers and self-service support for low contribution customers.
Defining business processes by customer segment is effective in growing revenues and margins from high contribution customers and lowering cost to serve for low or negative margin customers. The below illustration is an example of how customer segments may align with business processes.
In the above example, customers are segmented from most to least profitable. Mapping low contribution customers to lower cost business processes plugs profit leaks. Reducing costs to serve these customers creates an alternative to discontinuing these customer relationships. CRM software offers capabilities to lower cost to serve with tools such as customer self-service portals for sales order and returns processing or self-service knowledgebases, possibly with bots or virtual agents, for customer support.
Customer segmentation also supports revenue uplift strategies such as look-alike accounts and revenue prediction with sensitivity analysis whereby account segments can be modeled to understand the financial impact if the company increases or decreases customer churn by a given amount. Once you have a baseline measurement, you can devise CLV growth strategies that can be compared and selected.
A common mistake in customer segmentation is to group customers solely by their upside potential to the business and without regard to what these customers want from their suppliers. You can't deliver differentiated customer experiences consistently or at scale if you don't know how to delight your customers.
The research is clear in showing that customer insights highly correlate with higher sales win rates.
Customer insights are persona-based intelligence that reveal when, why and how customers make purchase decisions. Insights provide guidance to know what's most important to the buyer and allow the seller to focus on advancing the buyer's purchase process.
Insights are not data, facts or statistics; these are all knowledge. Insights are the reasons, behaviors or learning behind the data, facts or statistics. The dictionary defines an insight as "seeing below the surface." Insights deliver new learning and something that teaches and induces action.
Where customer segments are created based on who the accounts are, insights are created based on what they think. Insights are developed from market research and customer conversations which capture their goals and experiences and uncover their emotions, behaviors, attitudes and journeys.
Insights are used to deliver more targeted messaging and craft better sale strategies. In fact, the quality of your sale opportunity win plan is equal to the quality of your customer insights. Without customer insights your customer strategies are essentially based on assumptions or guesswork.
Once you know how your product is valued by each persona at each stage in their purchase process, you can create a repeatable Go-To-Market model that delivers more relevant and personalized content, connects with precise value propositions, optimizes marketing investment and delivers the most salient customer insights to the sales team.
As shown in the below example I created for a technology company, buyer insights are best delivered in the CRM system with the Contact record, but the data also flows into the qualification process and the Opportunity record sales win plan.
360 Degree Customer View
The often quoted but seldom realized 360° customer view is the asset to deliver customer intel when and where it can be used.
Customer Relationship Management is a business strategy aimed at growing mutually rewarding and profitable customer relationships. This strategy is dependent upon customer data. CRM software can create a holistic customer profile record built on five types of customer data.
- Demographic data is account and contact socio-economic data. Most companies track company firmographics (size, industry, location) and contact characteristics (title, role, contact information). Demographics are explicit data. They provide context around ability. They may define whether an account is in your ICP or target market. While they are a common starting point, demographic data are relatively stagnant and not good predictors of customer behaviors or contribution to key performance measures such as revenues, profits and lifetime value. Customer demographic data depreciate at about 2% per month.
- Transaction data includes marketing communications (offers accepted, rejected), purchase history (sales, renewals, returns, etc.), customer service history (cases, problems, resolutions), customer satisfaction measurements (NPS surveys) and other customer-specific transactions. Most companies allocate their scarce time and resources across customers regardless of customer contribution. A best practice is to append customer records with financial and other transaction data and reallocate effort and investment to customers based on their contribution to the company. The fastest method to an uplift in margins and profits is to steer investment and services toward the most profitable customers.
- Environmental data includes second or third-party data used to create richer customer profiles, link consumer relationships, establish house-holding, and more accurately align company products to customers. CRM systems are increasingly offering or partnering with Customer Data Platform (CDP) or Unified Data Platform (UDP) tools to merge fragmented customer data into a single, central view.
- Behavioral data shows what content each buyer has reviewed, the products the buyer is most interested, how far down the sales funnel the buyer is or how a product is being used after purchase. Each time a prospect or customer visits your website, uses your mobile app or interacts with your social networks he is leaving digital footprints that can be harvested to understand their intent and behaviors. CRM software is used to track and correlate these digital footprints, identify patterns such as products of interest, score the level of interest, and link these interests and scores to the customer profile record in the application. Notification alerts can then be sent to salespeople or the data can be used for highly specific nurture marketing campaigns. Behavioral data provides context around purchase intent. While explicit (demographic) data describes how interested the company is in the customer, implicit data shows how interested the customer is in the company.
- Social data identifies sociological attributes for each customer. Companies use social listening tools to automatically harvest customer social data. Knowing what each customer 'Likes', retweets or comments on creates a highly specific customer social graph. When social attributes are appended to the CRM customer profile record, the company can improve customer segmentation, deliver more personalized messaging, offer higher fit products and deliver services that influence loyalty and CLV.
A 360 degree customer view enables predictive analytics. By tracking customer or customer segment history of communications, offers and transactions, you can model and extrapolate to calculate the highest returns for promotion response, offer conversions, new product launch acceptance or other customer facing scenarios. CRM systems can also apply text analytics, machine learning or AI to recommend the Next Best Offer (NBO) for a marketing campaign or Next Best Action (NBA) for an account plan or sale opportunity.
Creating a 360-degree customer view is easier said than done. Gartner reports that fewer than 10% of companies have a 360 degree customer view, and only about 5% are able to use this view to systemically grow their businesses.
The Point is This
Acquiring customer data is one thing. Effectively using it is another. The below illustration shows how each type of intelligence should be directed to accounts (companies), contacts (people) and sale opportunities in the CRM system.
The Best-in-Class marketing, sales and service organizations systemically develop data-driven and fact-based CRM customer intelligence to replace customer knowledge based on anecdotal occurrences, dated historical experience, plenty of assumptions and personal bias.
Better information improves sales win rates and enables better customer relationships by showing how to make the customer feel special, delighted, valued, rewarded and appreciated, and deliver relevant, personalized, contextual and predictive customer experiences. Using customer data to deliver differentiated customer experiences creates a sustainable competitive advantage.
Research performed for the Sales Excellence Report found another interesting correlation. Companies in the most competitive industries had a disproportionately higher use and benefit from customer knowledge. In the absence of product distinction, leveraging a customer distinction is a proven method to increase separation from competitors, and a substitute to the alternative of reverting to price for differentiation.