Will AI Ever Deliver Precise Sales Forecasting?

Sales forecasting is a huge business. If you can improve the prediction of a business-growth of your specific products, you can better staff your facilities, better stock inventory and eventually keep more margin in your income business account. But in order to do it right, you need to dedicate a lot of your staff’s time and focus, and even then the desired outcome is not guaranteed. Nowadays, 74% of huge B2B companies engage in a regular sales forecasting. And despite all of the put time and effort, a key to success in this craft still remains hidden. Researches show that 69% of the B2B companies describe their results as ineffective.

According to InsightSquared: “A sales forecast is a projection of what your sales team’s performance will be at the end of a given measurement period (typically monthly or quarterly), or how much business you can expect to close this period. For future planning, resource allocation, appeasing the suits on your Board and setting expectations, this is absolutely critical.”

Problem

But why if so many companies are involved in sales forecasting the results are so pathetic? Simply saying, most of the modern forecasting techniques lack precision and critical thinking. It can be easily proved if we look at one of the most popular methods today, which is weighted pipeline forecasting. Here is how this method works: you need to take a likelihood percentage of a closing deal to every sales opportunity in a pipeline and then multiply it by the revenue value associated with the opportunity. The sum of all the revenue values you get is, in fact, your sales forecast. But it is a common case when opportunities are not loaded early enough, or some deals are simply hidden under a radar. And scoring how likely those opportunities are going to become deals is the main thing you should accomplish while predicting your sales forecast. With all of that in mind, you do not need an expert on your side to point out, that those hidden deals can lead to some serious forecasting errors. Such predictions can cause some serious damage to the company’s finances and position on the market. And in either case, the will not be fulfilled and trust will be lost. All the data and everyday experience should be taken into consideration as a result. Transparency make predictability.

Solution

Forecasting should be treated for what it really is, and that is science. Without a scientific reasoning behind it, prediction often falls onto two opposite ends of a spectrum, either the results will be very optimistic, or – very pessimistic. And either of the scenarios will have a serious impact on your company, its investments, and growth. There is a strict and precise method you should be following if you want to get the prominent results, and you should rely on your data and facts heavily.

This is where the Artificial Intelligence comes into play. It can be a force to reckon with when it comes to boosting the accuracy of your predictions. A recent research, made by the Aberdeen Group, that companies who can nail those accurate sales forecasts are 10% more likely to grow their business’ revenue year-over-year and 7% more likely to hit quota. Artificial Intelligence not only overcomes the most common problems of the weighted pipeline forecasting but also creates and improves many other successful techniques. Using AI in Sales forecasting B2B companies can help you achieve the following:

• Enhance lead scoring
• Accurate revenue forecasting
• Improve retention rates
• Improve close rates
• Better future planning
• Efficient resource allocation
• Maximize customer lifetime values
• Man-Machine collaboration to scale and sustain growth
• High-performing Marketing and Sales teams, with clear unified progression towards objectives

The biggest advantage of using AI to forecast your sales comes in form of a scientific conclusion, that you received by analyzing your data properly. This means that you actually know how you got your results and that you can apply it in the future. Accurate prediction is great of course, but it is even better if you know how it arrived. You should always be able to understand the rationale behind your numbers, otherwise, the prediction will not be useful, even if it was correct. This is the way we learn. So next time, making a prediction you will be able to correct your mistakes and improve your business as a result.

I also appreciate the fact that AI is brutally honest. It tells you everything as it is, and as a result, it helps you to learn and adapt faster.  You will need to have great patience but it will eventually pay off. AI will never forget about your losses and successes. And more data and coaching will only make it better.

So let us look now at the top companies in B2B that are completely transforming the way you use sales technologies by delivering Artificial intelligence in sales forecasting.

Salesforce

Research made by Salesforce themselves found that, by the year 2020, 57% of B2B customers will switch brands if a supplier company fails to actively anticipate their needs. And Salesforce is ready to help them keep their customers. Last year they introduced the Sales Cloud Einstein Forecasting, celebrating the first anniversary of Salesforce Einstein. Salesforce Einstein Forecasting is among the most reliable and powerful self-learning sales forecasting channels out there. This AI in sales forecasting tool is capable of instantly making highly accurate sales forecasts. The Salesforce for sales forecasting combines data mining with AI and ML to analyze, process and understand the key factors of what makes sales forecast extremely accurate.

People.ai

This company leads the pack of sales technology businesses that provide AI in sales forecasting tools. With a clear objective to apply AI and machine learning to the process of predicting costs and revenues associated with your sales activities for a given period of time, People.ai turns your traditional CRM into a completely new tool of analytics and high productivity.

Interloop

This company was recently featured in an IBM Watson case study. It is an AI-driven sales forecasting and intelligence platform for modern sales teams guarantees you predictive sales analytics, combined with insights and tools for specialists in the field to take immediate action if needed.

Adain Aiken – writer, editor, columnist, and proof-reader, who has worked in both the B2B and the B2C sectors. Bachelor’s Degree alumni of the University of East Anglia.