This is a guest post from Karen Hayward, CMO of Chief Outsiders
In the last decade, we’ve seen a huge investment in CRM infrastructure, processes and data collection. While these activities have been helpful, they have fallen short of illuminating real insights and helping organizations make better decisions to accelerate revenue growth. Understanding your own unique business drivers, revealing insights, and being able to drive actions using predictive analytics to make better quality and faster decisions are the next steps in operationalizing CRM. AND, being able to do so without the need for a huge sales operations team and infrastructure investments would make it feasible for even a small business to take itself to the next level.
Relying solely on CRM reporting and analysis has been limited to mostly manual number crunching based on history as calculated by a sales or marketing analyst. This is laborious and oversimplifies the complex selling/marketing process. We are hearing so much about big data and its possibilities, but big data analytics and actionable insights have been mostly elusive to the mid-market CEO and their leaders due to the specialized skill sets and the high cost of entry.
According to a recent IDG research study, 70% of enterprises made big data investments in 2014. These investments have the potential to change the way companies manage customer relationships by offering businesses powerful new opportunities to identify sales opportunities and optimize their go-to-market strategies based on propensity to deliver revenue versus historical performance. What is exciting for today’s mid-market CEO is the emergence of SaaS based platforms that offer an economical and perhaps more importantly a practical way to access this critical infrastructure, expertise, and established processes. There is a wealth of information in your CRM data, but to date it has been hard to extract data-driven actionable insights as simple charts only consider one or two factors at a time and do not recommend actionable next steps.
Using CRM to Actually GROW Sales
New Modeling SaaS solutions are making adoption of such analytics possible and revealing insights not seen before. It is clear that using CRM is simply not enough to wring out the true value of all of the customer data a company collects. While it tracks, manages, and reports, it significantly lacks the abilities to plan, forecast, and optimize that data to reveal insights that are actionable, and are the revenue accelerators in a business.
Four key questions that you need to be getting answers from your data to grow sales:
Taking your CRM data to the next level will enable a leadership team to uncover insights that allow them to use their data as a strategic asset, answer key business questions, and deliver real-time insights for the leadership team enabling better decisions based on data. Most organizations have plenty of domain knowledge. However, they lack data expertise, analytical acumen, model building capabilities and most importantly results interpretation abilities.
One such company that addresses this void is Acuity Sales Decision Science (www.AcuitySDS.com) – I had a demonstration of their SaaS solution recently and came away impressed with its ability to help a mid-market company take a scientific approach to their go-to-market strategy by using the following:
- Predictive Forecasting
- Opportunity/Lead Scoring
- Goal Attainment Probability
- Action Recommendation Engine
- Deal Closing
- Prospect Targeting
- Customer Retention
- Up-Sell/Cross Sell
A use case many of us can relate to is tied to our marketing initiatives and drip campaigns. We send outbound content to prospects daily, but don’t know what content will most likely cause the recipient to take action. By modeling historical campaigns and customer behavior, Acuity SDS can provide insights into which content will have the highest probability of being acted upon by a prospect, and if they are already customers or partners, which content is best suited for each.
A second use case is for inside sales. Do you know why your reps call certain accounts before others? Most reps use their experience and any BI-identified historical trend to filter their lists. Acuity SDS models customer, lead, and behaviors and uncovers signals correlated to customers buying. By applying those data driven findings to leads and opportunities, a smart list is generated that focuses reps on companies with the greatest propensity buy.
Imagine that your company could actually use statistical modeling to find insights that increase sales, and do it simply, without having to hire and train a whole data science team. Wow. That’s a giant step towards realizing the promise of CRM – to increase sales.