Want repeat business? Learn how to find the customers that are likely to buy more and buy again.
Finding opportunities to cross-sell and upsell to businesses already in their customer base can help B2B companies enhance customer loyalty, sell more products and services, reduce the cost of sales, and drive revenue. But determining which customers are ready to renew and buy more can be challenging.
Cross-selling is usually defined as discovering new applications for products and services that customers are already using. It can mean forging relationships with different departments within the same company or with companies tied to a client, such as a subsidiary. Upselling generally means increasing the size of existing orders by adding more units, upgrading a product, or extending a contract.
Upselling and cross-selling can help create stickier relationships by securing bigger (and potentially more complex and longer-lasting) commitments from customers. Despite the advantages, marketing and sales teams may feel reluctant about pursuing such opportunities. Why?
While most want their customers to consider them a trusted advisor, data gaps or data quality issues can limit their understanding of customers’ needs. That can result in the wrong conversations, irrelevant conversations, or conversations that occur too late to help sustain and grow the relationship.
View Customer Relationships More Clearly
It’s a painful truth: Customer data ages, and when it’s neglected, it can become too outdated to be reliable. Dusty, disorganized, and incomplete information can hinder the efforts of marketers and sellers to identify their most profitable and promising accounts to focus on.
A solid foundation of comprehensive, current data helps companies create a 360-degree view of customers – a view that can support more effective targeting and engagement tactics by marketing. It also helps supply the buyer insights that sales teams need for more successful pipeline-building.
To construct this view, companies need to implement a robust and collaborative data management policy. They also need to strengthen their existing database with third-party data from a trusted data provider.
First-party data – information typically collected through sales, marketing, and/or customer service interactions and stored in internal systems designed for customer relationship management (CRM), enterprise resource planning (ERP), or master data management (MDM) – tends to be the bedrock of a customer database.
When merged with third-party data – commercial data acquired from a trusted outside party – the result is fresher, richer customer intelligence that can be flowed into a modern sales analytics platform (such as D&B Hoovers™) to generate meaningful, actionable insights. Those insights can be leveraged for more effective strategies that help reduce customer attrition, boost customer retention, and streamline account management.
Strengthen the Pipeline
High-quality customer data coupled with powerful sales analytics can help automate the maintenance of account information. Together they assist marketing and sales teams with analysis of multiple data inputs and identification of customer accounts with a high propensity to renew and purchase more services and solutions.
More specifically, they can provide capabilities that include:
Pipeline visibility and management – A sales pipeline is a visual representation of every stage in the sales process from lead generation to close, providing a detailed picture of where each account stands in the buying journey. By sharpening this picture, strong customer data and sales analytics help salespeople determine how far they are from closing deals and what activities may help move deals along the pipeline. In addition, this improved view helps managers more easily monitor their team’s progress.
Predictive lead and account scoring – Traditional lead scoring usually is conducted by a marketer who manually analyzes the behavior of inbound leads, but predictive lead scoring applies a predictive analytical model to this task. It efficiently analyzes past data from a CRM system, maps a pattern based on a company’s past conversions, and gauges the likelihood that an existing account will purchase more or renew by assigning it a score.
Prescriptive sales activities – With a strong data foundation, sales analytics technology can build on the identification of patterns used for scoring leads to ultimately prescribe an effective sales technique based on the customer’s behavior. For example, based on contact and conversion data, an email (rather than a phone call) may be predicted to generate a more positive upsell or cross-sell outcome with a particular customer.
Predictive opportunity scoring – This scoring technique prioritizes sales opportunities by using predictive modeling to analyze account history and activity in a company’s CRM system and then determining which opportunities are most likely to be winners. This allows marketing and sales teams to focus on deals with a higher potential to close, instead of spending more time and energy on accounts that are unlikely to buy.
Predictive forecasting – Data and sales analytics can help automate sales forecasting, pulling a greater number of factors into calculations and predicting revenues with greater speed and accuracy than other traditional methods.
Together, data and sales analytics can generate actionable insights that support more successful customer targeting and segmentation, lead generation, and pipeline acceleration. That’s good news for marketers and sellers who need to increase customer engagement, reduce churn, grow market share, and help drive revenue.
Best Practices for Stronger Relationships
To better understand customers’ objectives and reveal who the most likely or ready buyers are, organizations can use data and analytics to dig deeper into customer account trends, account behavior, and previous sales outcomes. The following are a few of the areas of interest that can help marketing and sales develop more customized and competitive approaches to renewals, cross-sales, and upselling.
- Which customers have gone through recent economic challenges? Which have remained stable?
With this information, marketing and sales teams can prioritize cross-selling and upselling efforts more quickly and effectively. - What do recent wins look like?
Find and analyze new customers’ demographic and industry characteristics to spot commonalities, and then use those to identify potential look-alike buyers within other established customer accounts. - Do existing customers have a parent or sister company with similar needs?
If you already have a foot in the door, use it to your advantage. Check for relevant company linkages and turn them into opportunities. - Which contacts played an integral part in recent customer wins?
Review contact data to get a feel for their job titles, technological needs, and, most importantly, the challenges their job presents. Apply those insights to other established customer accounts and discover potential contacts with similar titles and needs. Pay attention to how many contacts were involved, as buying groups or committees may be heavily involved in purchase decisions and deals.
Remember that Buyers Are People
While data and analytics can help marketing and sales teams do amazing things, keep in mind the one thing they can’t do well: Make buyers feel heard, appreciated, and valued.
Data and analytics can offer an empirical assessment of customer needs, but genuine, active, and personal interest in a customer’s business journey and experience may ultimately be the most important component of any cross-selling or upselling strategy. Working as a concerned partner, and not simply pitching products, can help marketing and sales teams establish deeper connections with buyers and earn lasting customer loyalty.
Ready to learn more? Dun & Bradstreet’s guide, “The Data-Driven Way to Build Deeper Customer Relationships,” offers more tips for leveraging high-quality data and analytics to uncover new opportunities with existing customers and find new prospects inside established accounts.
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The information provided in articles are suggestions only and based on best practices. Dun & Bradstreet is not liable for the outcome or results of specific programs or tactics undertaken based on your use of the information. Please contact an attorney or financial/tax professional if you are in need of legal or financial/tax advice.