Subscribe

Use analytics to set sales targets that are on point

Kevin van der Merwe
By Kevin van der Merwe
Johannesburg, 25 Oct 2022
Kevin van der Merwe
Kevin van der Merwe

Whether we know it or not, we are all in sales, from the first line ambassador of the business − the receptionist − through to the CFO and CEO… everybody in the organisation. Without sales there are no customers, no revenues, hence no profit − essentially no business.

Sales truly fuel every function of the business. If sales are the lifeblood of every business − and they are − data, analytics and data literacy can be described as the fuel on which all businesses run.

So, bearing that in mind, you might ask why sales are the poorer cousin when it comes to establishing a data-driven culture and decision-making processes.

Many companies set sales targets often based on past performance and what they decide they need in terms of revenue − basically a thumb-suck.

But ask yourself how many businesses are capable of reading data and applying valuable analysis to the process of achieving insights to support sales target setting. The answer is very few, and this is despite seeing see other business units in the company, like finance, taking centre stage in terms of the use of internal and external data.

In the ultra-competitive world of sales, it makes sense to ask if there is a competitive advantage to be gained by becoming more data-driven.

Typical challenges faced by sales leaders

Forecasting: If sales are the lifeblood of the business, then pipeline is the lifeblood of sales. Nothing gets sold if clients don't know about the company and how the benefit of its solution speaks to their business goals.

However, not every customer approach leads to business yield, so it is essential to understand the volume, variety, velocity and quality of the pipeline.

As the old adage goes, you can only manage it, if you can measure it. Accurate and detailed forecast reporting is essential. But understand, reporting is only half the picture.

Gap management − budget versus target, versus actual returns

On any given day, if companies are unable to say how they and their teams are stacking up against budgeted targets, it’s likely they will discover they have a problem and one that is too late in the sales cycle to correct.

In a dynamic environment, companies need to be able to track how strategy execution is tracking to plan and make small, incremental, or sometimes radical changes to get back to plan.

Value proposition and changing customer trends

Sales trends and changing spending patterns can reveal leading indicators that there are challenging areas that need to be addressed (value proposition training) or changes in buyer behaviour. The data often lives on different source systems so standard customer relationship management application reporting won't do the trick on its own. A more holistic view of both customer and team behaviours is required to identify problem areas and modify to maximise return on sales effort.

Many companies set sales targets often based on past performance and what they decide they need in terms of revenue − basically a thumb-suck.

So, what are the different types of insights needed by sales leaders? The starting point for all sales analytics is a reporting (semi) static view of data − this serves to identify potential issues.

Once these issues are recognised (this is the what), you need to get to the potential root causes (the why) and manage them for better outcomes.

It is for this reason that an analytics dashboard is a great tool for the sales leader and the entire team. It allows the sales professional to self-service in a safe, familiar and governed way, but at the same time get to insight and intelligent action quicker than the competition.

This continues improvement in strategy and execution and can often mean the difference between winning and losing.

Customer intelligence: The pace of change is head-spinning, and what made us successful yesterday, won't work tomorrow. The only way to keep ahead of the pack is to adapt the offering, product, communication and strategy to the changing patterns of the market. Aggregating data from various sources is an essential element of a good sales intelligence system.

Advanced analytics: Hidden patterns in the data often reveal insights that are too complex for the human eye to detect. Spotting those patterns and relationships in the data can provide a valuable competitive advantage that can identify and highlight new opportunities, improve existing processes, provide client intelligence and mitigate risk.

Advanced analytics and machine learning can be particularly useful to take advantage of this opportunity hiding in the data. For example, using graph analytics enables the company to spot relationships and pinpoint the strength of them between entities.

This will help to direct it to the more influential and highly connected individuals in a network. This, in turn, will allow better target prospects for business development efforts.

These are some of the key elements of a sales intelligence system that every sales leader and professional should have access to if they are to remain competitive in a fast-changing world.

It is not critical if the firm doesn’t have the full capacity overnight, but if it is still trying to manage the sales function and team by Excel or reports, it may be time to consider what the next step in the sales analytics evolution looks like.

In my next article, I will reveal the important role of data literacy in an organisation.