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4 effective ways to improve accuracy in sales forecasting with AI

Engati Team
Sep 15
4-5 mins

Table of contents

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AI in sales forecasting

Sales forecasting is immensely important, irrespective of the business you’re in. It helps organizations protect themselves by spotting and fixing issues in advance. It even helps them make informed decisions regarding budgeting, hiring, and goal setting. But, as important as it is, most businesses are far from accurate in these matters. Here’s where AI comes into the sales forecasting game.

The actual situation

Most businesses are currently unable to make sales forecasts that are even close to being accurate. 69% of businesses think that their efforts are ineffective.

The fact of the matter is that only around 28% of sales forecasts are even vaguely accurate. 47% of 90-day predictions were off by a margin greater than 50%.

The Aberdeen Group found out that companies with accuracy in sales forecasting had a 10% higher likelihood of growing their revenue year-over-year.  They’re also 7% more likely to hit their quotas. 

But, to get there, companies are definitely going to have to step up their game and make some major changes.

Why are sales forecasts inaccurate?

why are sales forecast inaccurate

Great question. There are a number of reasons behind that. Here are a few of them.

Over optimistic sales representatives

Sometimes it feels like your sales representatives breathe optimism instead of oxygen. And that’s not essentially a bad thing. Being optimistic actually helps them perform better.

The only issue is that their sales forecasts tend to be way off.

Lack of clean data

If you don’t feed your databases with accurate and high-quality data, your forecasts are going to be far from accurate. According to a study conducted by Experian, 91% of businesses have data errors on their hands.

MECLABS’s Brian Carroll put it best,

 Garbage data in, garbage results out

Human error is the leading cause of data inaccuracy. Automation would help spare your employees the efforts involved in data entry, save a lot of time, and reduce inaccuracies. 

Employee churn

If members of your sales teams leave your company, revenues are going to dip. If they leave unexpectedly, your sales forecasts will once again be off the mark.

Your competitors

If your competitors make any major changes, it’s likely that your own sales will be impacted. If they drop their prices, you may have to reduce your own prices or risk losing business. 

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How can AI help in sales forecasting?

ai in sales forecasting

Data processing

Businesses generate tremendous amounts of data on a daily basis. But, processing this data is really hard for humans. There's just too much historical data for humans to go through on their own.

As a result of this, we just ignore a lot of our data. Valuable data is discarded because it's too much to process. This means that we're making uninformed decisions. And that's causing inaccuracies.

AI can bolster your sales forecasting efforts by going through the data and providing your staff with insights, observations and suggestions improving the overall sales process.



Internally deployed chatbots can help your employees make better forecasts. These bots could help your employees gather data and information from your system with minimal effort.

Instead of spending their energy hunting through your systems, all they'll have to do is send a message and the bot will retrieve that information for them.


Lead scoring

AI & chatbots can even help with lead scoring. The user information collected by chatbots can help in scoring the leads in a better fashion. Artificial Intelligence can help understand which leads are more likely to convert. This can help improve forecasts and help sales reps concentrate on the right prospects. Here's an insightful article on sales prospecting techniques.


Predictive analytics

Predictive analytics go through the information available, analyze patterns and make predictions based on these patterns. They incorporate AI, data mining, statistics and machine learning to create predictive models.

Entrepreneur Magazine reported that organizations using predictive analytics have been able to make forecasts that are up to 82% accurate.

Start making better predictions

AI and machine learning can be very valuable tools for increasing the accuracy of sales forecasts. The early adopters of these methods will certainly be able to make better predictions, leading to better decisions.

Get started with Engati's AI offerings and start improving your sales forecasting accuracy today.

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