The most successful sales organizations do a precise job of getting in front of the right buyer at the right time with the right solution. While companies invest large amounts of money in supplemental data and predictive analytics tools, we often see this being an under-utilized asset for sales. Applying Artificial Intelligence (AI) for Sales Planning can be a powerful capability to provide intelligent insights on where to focus sales efforts to help achieve revenue goals.
In our current economic uncertainty, these insights can become even more vital for businesses. Historical patterns of sales are being disrupted, so old methodologies such as targeting by industry and size of the company will not cut it. Companies need to supplement such firmographic data with buyer intent insights based on real activity in the target company. At Spaulding Ridge, here is how we help our clients identify some practical uses of AI with Anaplan, applying the data meaningfully in order to better inform, predict, and enable their sales organization.
As the business environment due to the COVID-19 health crisis continues to evolve, we expect at some point different companies will start to come back ‘online’ and be looking for new solutions. However, each company will behave differently. Sales organizations that can pick up on these buying signals quicker will be at an advantage when economic activity increases again. Below, see some practical advice for using predictive insights to drive your sales plans and activity:
Start small, focus on a few areas first to make them actionable. Too much data at once can be overwhelming ” making it hard to manage and measure. Identify the low hanging fruit that can bring value to the sales organization immediately, and then add & adapt over time. As the economy shifts, so do the analytics, so implementing with an agile approach is crucial.
The Low Hanging Fruit
Where do you start with utilizing AI intelligence? Outputs such as buyer propensity to buy, TAM, and new prospect recommendations can help narrow sales teams focus on key target customers. This data, along with subjective inputs from sales teams can be weighted and calculated to determine relative account scores. A data-driven and collaborative account scoring process can inform sales on which accounts to initially focus or prioritize. In addition, it catalyzes to support downstream planning and modeling, like determining which accounts, and how many the sales reps should cover. This helps to ensure there’s equitable territory alignment and optimal account coverage to increase overall productivity across sellers.
Measure the Results
What’s working this year may not be what works next year, or even next week. No matter the sophistication, or lack thereof, it’s imperative that each planning cycle you measure your results and continue to iterate. Did I sell where the data said we would sell? What worked and what didn’t? Why did we overperform or underperform in certain industries, geographies? As customers’ needs evolve, you should adapt as well, and predictive data intelligence can enable you to adapt and identify these behaviors quicker.
At Spaulding Ridge, we have been working with our clients with platforms such as Anaplan and Salesforce to (1) identify the most attractive accounts to target, (2) deploy sales people and territories around those targets, and (3) drive sales execution by feeding real-time insights to reps that improve their likelihood of success. Now is the time to invest in these solutions–while for many, demand will be down for some time, developing an approach now will set companies up for success as we eventually recover.