Sourcing new outbound leads is a never-ending endeavor for sales and marketing. Prophesies of cold calling being dead have not come true if only for the simple reason that prospecting through all channels must be on the table to fuel the engine of sales growth. Companies typically procure lead data from four main types of leads: Internally-generated leads: Referrals, word of mouth, events, etc. Intelligence-based leads: Newsfeeds, industry alerts, personnel changes, etc. InsideView is one good example of this, but we believe LinkedIn also fits this mold (the evolution of this is exciting) Special or vertical lists: Trade associations, commerce groups, organizations operating with a geographic charter Compiled lists: The likes of D&B and InfoGroup, including credit files But as any sales or marketing manager knows, simply dumping more records on a sales rep is a thing of the past. Lead nurturing and scoring are the norm, wherein prospects are nurtured until they raise their hands as hot leads, and are then forwarded to sales. In addition, predictive modeling that identifies the most likely prospects based on the “ideal customer” profile must be part of the mix. It’s clear that the prospects at the top of the funnel – the ones you might pay for – are not sales ready. Further criteria and …Read More
Tag Archives: ROI
How predictive analytics adds value during & after selection of your CRM system – Part 2
Yesterday we posted the first tip of how to use predictive analytics to make your CRM system even more valuable. Today we share several more tips … Retain focus on business objectives The excitement of implementing a tool that solves basic operational problems is understandable. The front-end responsibility of reliability, inter-operability and security is clearly with IT. These challenges are significant. But it is important to go beyond the technology’s bells and whistles. By establishing a vision for analytics – metrics, measurement methods, forward-looking indicators and performance management – and incorporating these in the design, the rationale for the CRM system and its ROI can be validated. Through predictive analytics, business processes can be mapped and modeled, and benchmarks created for delivering quantifiable goals to the enterprise via the CRM system. For example, is the primary objective of your CRM to support lead generation, product penetration or customer retention? Based on your needs, predictive analytics can help develop appropriate forward-looking indicators, expected results and diagnostics of the results at all levels of activity – customer, sales people, products and operational areas. This will allow ongoing correction and calibration of your activity within the CRM system that maintains the focus on the business outcomes, not …Read More
How predictive analytics adds value during & after selection of your CRM system – Part 1
Customer Relationship Management (CRM) systems are the currency of customer-sales interactions. Effective, simple CRM software helps sales reps to focus on content of conversations rather than the mechanics of conversations, resulting in sales empowerment and productivity gains. A CRM system can be a boon to sales people. CRM helps overcome the technology hurdle of accessing information over disparate systems. CRM systems help improve collaboration within, above and across the entire organization, allowing the company to speak with one voice. And from a governance perspective, these systems help elevate the customer relationship from individual dependencies to an enterprise-wide strategic asset. When you add the potency of predictive analytics, a CRM system can be even more valuable. Leaders in analytics, sales operations and technology can fulfill their obligation towards sales empowerment by creating a cohesive approach that brings these disciplines together. How well we achieve this determines if a CRM system just gains basic acceptance, or whether it is fully adopted and even embraced by sales people who realize its benefits for themselves as well as for their customers. Here are guidelines to help make that happen: Consider a multi-stage deployment In the first stage of CRM implementation, deliver base functionality to the users so that their immediate, tactical pain points are addressed. This often …Read More
Customer life stages, predicting customer outcomes and applying corrective actions: Three metrics to measure ROI
Customer life stage is the standard bearer of segmentation. Customer stages like “new,” “active,” “lapsed” and “lost” serve an important purpose by grouping customers into homogenous, manageable clusters for marketing, value measurement and investment decisioning. However, these definitions have limitations that you should consider and correct prior to sales applications. Here are key limitations and how to overcome them. Measurement windows are too broad: Most of these segments have a 6- or 12-month horizon for comparison. A “new” customer stays in that segment for 6 months, often regardless of spend or activity, whether based on total spend or number of orders. Similarly, a “lost” customer is usually defined as any spend in the past 13–24 months, but zero spend over the past 12 months. As you can see both the time and revenue windows are very large, and that dilutes usefulness. Regarding time, this can be a few weeks or up to 24 months, and regarding revenue, the measure can be a few hundred dollars to several thousand. Corrections: Create smaller segments for sales applications with sub-definitions. These can be arbitrary to follow a business threshold (i.e., 6 months or $2,000) or they can segment eligible customers into equal percentages, like 50-50 or 33-33-33 percent. Another option is to create “run-rates” based on …Read More