B2B Sales

B2B Sales Forecasting With Predictive Analytics

Do you ever feel like you’re scrambling to understand what your leads need? As your team crafts marketing campaigns, sets follow-ups, and constructs proposals, it would be nice to have some certainty that they are on the right path. 

Predictive analytics is a game-changer, especially the bottom up method for forecasting sales. Armed with the right tools and data, it’s possible to make more accurate predictions about what prospects want and need to become paid clients.

What Are Predictive Analytics?

You only need three things to leverage predictive analytics for sales forecasting: the right data, modelling techniques, and machine learning. With these tools, experienced analysts can identify sales patterns and predict when you can expect to see them again.

For example, an analyst might look over data for the past several years and notice an uptick in sales during the first two weeks of September. The marketing and sales teams can then prepare campaigns to align with those dates to capitalise on that trend and convert more sales.

Predictive analytics essentially provide more accurate forecasting and allow businesses to operate on a much larger scale to support sustainable growth.

How Predictive Analytics Support Sales Forecasting

Predictive analytics supports sales forecasting in four fundamental ways. 

  • Organise longitudinal data into meaningful reports that give you better pipeline visibility.
  • Allows teams to identify patterns at each stage of the sales process.
  • Leverage predictive modelling techniques to dig deeper into buying trends and make in-depth comparisons, so your team can make better decisions.
  • Ultimately, your team develops a more accurate sales forecast to streamline sales processes and increase conversion rates.

When sales teams embrace predictive analytics, they gain a better understanding of their customer base, leading to more relevant campaigns and proposals. You can also optimise your processes and resource allocation to reduce waste and increase profits. 

The Bottom Up Method for Forecasting Sales

The bottom up method for forecasting sales involves digging into data on individual components and then working up to the bit picture numbers. 

This approach allows you to see how all of the components fit together and each member's contribution to the whole company. It provides accurate, individualised information, so you can make minor tweaks at the base level immediately.

For example, you have a sales team of six people divided into two teams. First, you would break down individual data for each rep to get a clear picture of each individual’s contribution and impact. Then, you would work up to the numbers for each team, and finally, you would look at the overall company sales. 

Since this method requires accurate, robust data, using predictive analytics enhances the results and provides a clearer picture at every level.

How Predictive Analytics Support Sales Forecasting

Best Practices for Using Predictive Analytics

Leveraging predictive analytics for sales forecasting may require additional software and restructuring, but the results make it worthwhile.  

1. Use the Right Data

The first lesson of predictive analytics is that not all data is relevant, so you need to focus on quality as much as quantity to yield accurate results. It might be worth hiring a skilled data analyst to ensure you have the best data possible. Experienced analysts will know what to include and ignore.

Note that using a combination of historical and real-time data is best for building a successful model. If you already use Microsoft products, it’s possible to set up sales forecasting in Power BI to track both types of data.

2. Prepare To Adapt

Working in sales, you probably already know that things can change quickly. Regarding predictive analytics, it’s best to prepare for quick pivots based on new insights. 

Building adaptability into your workflow is a key step for teams using predictive analytics. You want to be flexible enough to make quick decisions and changes to reduce waste and boost the bottom line. Consider using a platform like Forward that supports real-time collaboration between teams.

3. Slow and Steady Wins the Race

It could be tempting to dive in and try everything at once, but it’s best to take things slow. Using predictive analytics can be a massive adjustment for sales teams, and taking on too much at once can backfire.

You might want to do your research and offer training to ensure the entire team understands what’s happening. It’s better to have everyone on the same page and experiment a little at a time. 

Leverage Predictive Analytics To Optimise Sales Forecasting

Predictive analytics is no longer a future trend, it’s the way of the present. Teams that embrace the bottom up method for forecasting sales gain more accurate, deeper insights into customer behaviours. Using that data and forecasting, they can adapt faster and make better decisions, reducing waste and leading to more conversions.

Forward helps sales teams use predictive analytics by supporting collaboration between teams and offering access to in-depth statistics from one dashboard. It’s easier than ever to access the data you need to gain insights into your customers.

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