How to get over 90% pipeline accuracy in B2B Sales Forecasts

Gartner research shows that executives report pipeline management and sales forecasting as one of the top areas where sales operations functions are least effective.

Consistently accurate forecasts are what promotions are made off!

In fast-paced B2B sales, Forecast Accuracy is driven by two essential techniques-

Qualification and Standardisation.  Today let's focus on Standardisation.

Why Standardisation is important in your sales pipeline

B2B Sales teams need a clear understanding of the specific pieces of information required before they can confidently move a deal forward to the next stage in the sales pipeline.  A shared understanding of what evidence is needed for a deal to progress through the pipeline simplifies sales management and increases forecast accuracy.
 
Without a standard view of what these essential pieces of information are, sales teams will interpret and, through best efforts, present an inconsistent pipeline. Imagine a scenario where one team member believes that customer budget is the most important factor to verify, while another team member focuses on the customer's decision-making process.

Both of these (along with four others) are all critical data points to qualify a deal and it's correct place in the pipeline. Only with a shared understanding of precisely what each of these six data elements is can the timing of each deal be correctly judged. Similarly, revenue projections can only be accurate if there is a consensus on the essential information needed for each stage of the sales process.
 
Let's walk through an example of applying Commonality to increase forecast accuracy.

Most CRM software solutions use simple multiplication to determine forecast revenue by multiplying the deal value by some arbitrary weighting. With only two elements to this equation, we have three options to apply commonality.

- Option 1 is to build some intelligence into the weighting percentage to 'curate' the forecast total.  
- Option 2 requires evidence at each stage to ensure the deal is progressing to close.
- Option 3 is a combination of one and two.

Option 1 is quite simple to implement. Changing the percentage associated with each stage of the pipeline can be an effective way to manage expectations. However, it does not solve for a lack of qualification.

Option 2 can help with various qualification issues by requiring evidence at key stages in the sales cycle. For example, if the customer has seen, read and understood any associated contracts, this clears several qualification hurdles and would be crucial 'evidence' for a deal to progress to the next stage in the pipeline.

Combining these two options provides sophisticated deal qualification and realistic tracking through the pipeline while coping with simple multiplication to calculate the forecast number.

A standard view of these crucial pieces of information is vital for a smooth and efficient sales pipeline, leading to improved forecast accuracy. By establishing a clear framework and guidelines, sales leadership can ensure everyone is on the same page and working towards a common goal. This improves efficiency and enhances collaboration and teamwork within the sales department.

A recent McKinsey study indicates that AI-based forecasting improves forecasting accuracy by 10–20 percent. This translates to revenue increases of 2–3 percent. An accurate forecasting system can also help determine ideal inventory levels and better predict the impact of sales promotions. 

HubSpot Sales Hub has successfully harnessed the power of AI integration to optimise forecasting processes. Sales Hub already has AI Sales Forecasts and  Predictive Deal Health Scores which means when you implement the approach we mention and update your processes, paired with AI tools in HubSpot, your forecasting is likely to be consistently more accurate.

Organisations that prioritise sales pipeline quality are 2X more likely to exceed customer acquisition expectations. Gartner

B2B sales journeys are dynamic and complex. They involve numerous stages, stakeholders, interactions, and variables. B2B selling involves a delicate balance between leveraging data science and building relationships. These complex sales opportunities are an intricate blend of art and science. It's part of the reason why so many sales leaders struggle with sales pipeline management and forecasting.

Having a shared view of specific pipeline evidence as 'stage gates' is essential for sales teams to present the sales pipeline accurately. By establishing a common understanding, sales leaders can ensure consistent timing and revenue for each deal. This improves efficiency, enhances collaboration, and allows for accurate forecasting.  

So, let's strive for a common understanding of what each pipeline stage means and what value is assigned at each stage to achieve high forecast accuracy.

Related

Learn more about improving your opportunity qualification in our blog article on the 12 Best B2B Sales Methodologies and Top 3 qualification frameworks.

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