This post was originally published on the Smart Selling Tools blog.
In today’s big data business world, sales reps often find themselves drowning in sales data and reports, rather than data improving their efficiency and effectiveness in selling. This is especially true for sales people who manage a large book of business and large product portfolios: the larger their account or product list, the larger the data sets to review and report on, and the less time they have to focus on growing and retaining every customer account.
Out of necessity, sales reps often make their day-to-day decisions based on historical precedence, existing pipeline and path of least resistance. However, this can result in less time uncovering the untapped potential hidden within their entire customer base.
Entertain this quick thought exercise: If a sales rep picks one of their customer accounts - it doesn’t matter if it’s one of the largest or smallest - what percentage of the total possible spend related to the goods and services your company provides have they captured? Could they capture more? If so, where and how? Can they quantify it, or even estimate it?
Most organizations will turn to quarterly and annual account planning to force this thought exercise. Armed with more and more data, graphs upon graphs, and documented in static, written documents and presentations, these methods simply do not equip sales teams with the information they need to win in today’s hyper-competitive markets.
The reality is that sales people do not have the time nor processing capability to identify the best upsell and cross-sell opportunities to expand wallet share across their entire account base. Further, while any rep will certainly notice a large decline in sales from an existing account, they will not pick up on signals that indicate when a customer might defect at the product level.
However, there are prescriptive sales analytics solutions in the market today that present data to sales reps in an actionable and timely way, streamlining their account planning processes and helping them to better manage their time.
First, let’s define prescriptive analytics. Forrester defines prescriptive analytics as using data and analytics to improve decisions and therefore the effectiveness of actions. While Gartner defines prescriptive analytics as a form of advanced analytics which examines data to answer the question “What should be done?”.
It falls under the same umbrella as predictive analytics and is a form of artificial intelligence. Unlike predictive analytics, prescriptive analytics goes beyond simply predicting what is likely to happen, suggesting a range of prescribed actions and quantifying the potential outcomes of each action.
For B2B sales reps who are stretched thin over many accounts, this is a seller’s dream. Imagine when a sales person logs into their CRM, they are presented with the top opportunities for upsell, cross-sell, pricing and are alerted to at-risk customers, across their entire customer base, all in a prioritized and manageable way.
Prescriptive sales guidance tells them who to call first and what to talk about. It shows them where their time is best spent, which improves their sales results and performance. This also saves reps time, because they no longer spend their valuable time digging through reports looking for the best opportunities within their account base. What used to take days to generate plans that were hard to action, can be replaced with an always-on sales assistant that is constantly analyzing all customer and transaction data, and feeding them with actionable opportunities when they matter most.
Prescriptive sales guidance also gives sales reps confidence when dealing with their customers. Instead of having anecdotes and limited information during a negotiation, they have fair-market insights for that account and all accounts like them. This type of insight helps reps always know and quote the right price for the right product and for every unique customer interaction. It raises the performance of all sales reps, and creates scale across large sales organizations to help underperforming reps perform more like the company’s best.
Many B2B enterprises are turning to prescriptive, AI-based solutions to help their sales teams drive the company’s financial metrics of revenue and profit. This gives them a competitive advantage, as well as a reliable and predictable means of hitting their goals.
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