A modern approach to consistency in the sales process.
A sure-fire method to extend the sales cycle, add confusion to the forecast, and lose more deals is to have an inconsistent sales process. Having too simplistic of a sales process is just as bad. Imagine if a recipe just listed “add ingredients, mix, then heat”.Ora football running play, like the counter, was described as “run, fake, handoff”. You would not have much success in the outcome of either of those scenarios. So, don’t expect much sales growth when you have a few general sales stages that lead a lot to the imagination. Your reps will be all over the place when they report deal status or provide a forecast. Your sales process has to be well aligned with the activity that goes into a successful sale. It should also help in making decisions on next steps and be consistently understood by the entire sales team.
According to CSO Insight’s 2015 Sales Enablement Optimization Study, those companies with “unaligned sales processes deliver conversion rates between 8% and 27%. There is also a significant negative impact on quota attainment. The difference in quota attainment between being unaligned and being mostly or fully aligned is 13%.”
But what happens when we get new sales people? Isn’t it hard to keep everyone informed on definitions and when to forecast? And considering that customer buying behaviors change, doesn’t that just exacerbate the problem?
Enter the new modern automation of machine learning algorithms and predictive analytics to simplify alignment and improvement of your best sales activity and give your organization the edge it needs to continue sales growth. So, before you apply automation and predictive analytics, first give yourself a sales process health check to see if you should give your process a tweak or an overhaul. Follow these four steps:
Consistent Lead and Opportunity Progress
Outline your sales process from lead to opportunity to close/won and lost. Identify what happens to a lead as it flows through the stages from initial suspect, to interest level, to its conversion to a qualified opportunity. Identify the exit criteria or milestones required to advance the lead through it’s stages until it converts to a qualified opportunity. Obviously, you have to define what a qualified opportunity is, usually related to identifying authority, need, urgency and ability to fund/budget. Then identify the stages to navigate the opportunity through the sales pipeline with the objective of getting alignment with your solution, handling objections and proving ROI and compelling benefits. In most cases, this outline process is easier than you think – just review the process with your reps and go with it. Then iterate while you’re using this process. Expect to see more blogs from me on how to outline and iterate your sales process.
Consistent Pipeline Health
How do I know which of our opportunities are real, which require some action or they will fall out, and which should just be removed? A healthy sales pipeline is much more than just tracking deal progress. We described deal progress as stages and milestones that the lead flows through and evolves into an opportunity and how the opportunity progresses forward until it is closed won or lost. Health includes two additional components – Ideal Customer Profile (ICP) and Momentum. Ideal Customer Profile includes all of the attributes of customers that buy your solution. This is typically defined by revenue, market, product modules, number of employees or users, roles, and other attributes related to the appropriate persona of an ideal prospect. Momentum includes all the activity and attributes that are required to close a deal in a reasonable time frame. Typically these include proper timeliness within a stage, acceptable activity with the appropriate roles, positive or negative check-ins (a “check-in” is defined as actual communication with the appropriate roles including meetings, phone or emails) and meetings scheduled (or not scheduled) for positive (or negative) momentum.
Consistent Forecast Categorization
Forecast categorization helps the sales team understand when a deal is ready to be committed to the forecast for the sales period. Examples of forecast categories could be as follows:
- Commit: Ready for Forecast to current sales period
- Upside: Positive momentum and probable to close, but may close in next sales period
- Engaged: Prospect is active with scheduled meetings and within reasonable timeliness of stages and possible to close in current sales period
- Stalled: Prospect is falling out of pipeline due to lack of timeliness of responses and/or no scheduled meetings going forward.
These categories should be fully defined and understood by the entire sales team based on health of the opportunities. Rules should be defined and categorization should be automated.
Applying Automation for Consistency
Modern automation applies machine learning algorithms and prescriptive next steps to keep everyone aligned – even the new rep that’s ramping up. This will ensure everyone’s doing the same things so outcomes are more predictive.
Because machine learning may require a few sales periods to learn the sales process, rules should be set based on tribal knowledge to alert sales teams on deal status and guide consistency. But eventually, as the process is analyzed over time, machine learning algorithms will kick in and suggest additional metrics and activity to watch and prescribe next steps even when customer buying behaviors change.
By applying this kind of rigor around process consistency, better analytics will happen for performance improvement. The most notable benefits of a consistent sales process injected with machine learning and predictive analytics are:
- Sales Cycle Time reduction of >38% with prescriptive next steps
- Forecast accuracy of 85% to 95% (from CSO Insights statistic of <46% accuracy)
- Increased wins by ~25% due to focus and applying resources and time on the right deals
- Time savings of 11 hours/week to get a handle of the pipeline and forecast
To learn more about how TopOPPS can get your team on a consistent sales process utilizing predictive and prescriptive analytics, please contact us at email@example.com.
Up next – Predictive Analytics for Forecasting