Aligning your pipeline with the buyer's journey - is it a good idea?
Aligning your sales pipeline with a sales view of your buyer's journey is a smart move. Seriously, it's a no-brainer. Not only does it guarantee...
4 min read
Peter : Sep 25, 2023 10:05:16 AM
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.
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 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.
They can identify potential bottlenecks or areas for improvement, enabling them to make informed decisions and allocate resources effectively.
With a consistent approach, sales teams can also provide accurate forecasts, helping the organisation plan for future growth and success.
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.
A sales pipeline serves as a valuable tool for sales teams, aiding in the management of opportunities and revenue predictions.
On the other hand, a sales forecast acts as a forward-looking projection of sales revenue. The key distinction lies in their functions - the pipeline focuses on current opportunities and operations, while the forecast is strategic, aiding in future planning.
AI excels in managing vast amounts of intricate data and has the ability to analyse historical data to recognise patterns.
In order to maximise the potential of AI for sales forecasting, companies should integrate it with effective data management strategies and strong cybersecurity protocols, while also meticulously reviewing the results to align with your own forecast perspective.
Qualification can assist salespeople in pinpointing the deals they have a higher chance of winning.
This process helps save valuable time and resources, enabling sales teams to focus their efforts on prospects who are more likely to make a purchase.
While they are linked, they are not the same.
In essence, if you consider Demand Forecasting as the broad perspective for your business, then Sales Forecasting serves as the detailed perspective — assisting you in planning for particular time frames.
Although many businesses develop forecasts for the entire year, you might prefer to forecast on a monthly or quarterly basis, based on the current activities within your business.
Also worth mentioning, Sales Forecasting and Sales Pipelines are often used interchangeably but they are NOT the same thing...
For valuable insights into growing your business in challenging conditions, tune in to the Unicorny Podcast with special guest - none other than our Head Honcho, Peter Russell-Smith and Podcast Host, Dom Hawes from Selbey Anderson.
It a cracking episode! Listen now
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