Why every enterprise needs AI-powered sales forecasting

Business leaders are being challenged to become more flexible and adaptable than ever before — yet are being held back by their lack of insight and ability to forecast sales and revenue. Many enterprise functions have simply had to undergo a rapid digital transformation to function in the new world, and the sales team is no different.

In a time of uncertainty for business, the key question many look to ask is ‘What kind of leadership do we need now?’ The most common responses are typically ‘adaptable’, ‘flexible’, and ‘innovative’. A recent Forrester report titled “Unleash your Growth Potential with Continuous Planning”, highlighted why these leadership types are so key but why many are being held back.

In the online survey of 352 B2B sales, finance, and other business leaders, more than 85% of respondents were aware they must take a continuous, data-driven approach to sales planning, but most weren’t making the technology changes they needed to do so. While 90% said that making real-time decisions based on real-time insights is essential to be effective, the lack of the right technology to do so was holding them back.

Artificial Intelligence (AI) has the potential to pave the way in bridging the technology gaps in sales and business planning. Using a data-driven approach can turn data into actionable business intelligence with the ability to course correct in uncertain times. Here are four ways utilising AI can help boost enterprise sales and planning efforts. 


1. Dig-in to your data

Data is your biggest asset in the information age. Sales leaders may begin to feel that forecasting and insight is impossible to achieve in the current climate of unpredictability, but all you need are the real-world insights data provides and a tool to help bring it together. With leaders under pressure to improve sales performance across the board and support the business through turbulence, having a sidekick in the form of data can help in optimising sales performance.

Working with a technology provider often has benefits beyond the implementation of the product, too. Data insights are sometimes hard to come by if you haven’t had your ducks in a row previously, but utilising benchmarking and market data from technology partnerships is essential to business planning. By using data such as market pricing for a particular product or service, or geographical spikes in sales, sales leaders are able to better understand how they are operating compared to industry trends in these ever-changing times. And who better to partner with than a technology company using AI to dig-in to the data and keep you one step ahead of the game.


2. Be flexible and deploy changes quickly

It’s no longer appropriate for a wait-and-see approach to transforming your sales strategy. The pandemic has accelerated the need for agility and investment in digital transformation has become paramount to success. It’s therefore time for growth leaders to become adaptable, which can now truly be achieved by harnessing the power of data-driven insight.

By using AI to highlight real-time performance insights, enterprises can drive rapid deployment of sales strategy changes and targeted incentives to a broader audience, uniting strategy and execution for increased quota attainment and top-line growth.

So, while AI might seem like a tool for the IT department, enterprises can actually increase top-line revenue with better organisational alignment and insight. These are the wider business benefits AI offers and the sales team should be pioneers to make this change happen. After all, they’ll be able to deliver a clear business benefit through increased revenue.


3. Managing resource and capacity planning more efficiently

Losing valuable employees is a concern for every organisation, especially in the new world of work where anyone can work from anywhere. Your top performing sales reps are perhaps the most crucial of all and there is no doubt that the ability of a sales team to reach its targets depends on having the right number of reps closing the right deals. By pulling data from an existing Customer Relationship Management (CRM) system, AI applications for sales can use pay and performance data to predict how likely an employee is to leave the organisation. The ability to forecast, with both employee retention and the sales pipeline, has always been important but the requirement for accuracy in forecasting has never been such a necessity until now.

AI-powered sales tools can also highlight both high-performing and underperforming salespeople based on a variety of indicators. These applications can review CRM data automatically, checking for sales reps whose performance has dropped or who have been receiving low pay checks. That way, sales managers have the information they need at their fingertips to make changes to the team. The benefits of AI not only empower your sales reps to perform with data-lead insights, but nurture and protect the stars of the show, building a team of top-performing and more importantly happy salespeople.


4. Reduce territory planning time and cost

Planning which territories each sales rep controls has always been a challenge, in the era of remote working, this becomes even more confusing. AI for sales can leverage customer data from an existing CRM to construct optimised sales territory plans and even predict the optimal number of sales reps required to cover territories during a new product launch. AI allows sales organisations to consistently design territories that are balanced, efficient, and give reps equal opportunity to achieve and exceed their target.

Many enterprises wish they had their data houses in order, but most unfortunately do not. However, the days of gut-level decision making and intuition bias are well behind us. Growth leaders need to leverage best-in-class sales AI tools that help them quickly ingest information and turn it into actionable business intelligence they can use to course correct or maximise their sales potential.

Jamie Anderson

Chief Sales Officer, Xactly

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