ROI and measurement for sales
Measuring AI ROI in sales requires tracking leading measures like meetings held and proposals submitted, as a sales manager checks the team's activity log to see if the new strategy is being executed, and comparing sales by product or region to understand the intervention's impact.
Can we really measure the return on investment of a sales intervention, or are we just guessing at the counterfactual, wondering what would have happened if we had done nothing? This question comes up in every meeting where a sales team is considering a new strategy or tool, and it is hard to answer because the counterfactual is invisible - we can never know for sure what would have happened if we had not intervened.
Leading measures you can actually observe
In practice, this means we focus on leading measures that we can actually observe, such as the number of meetings held, the number of proposals submitted, or the number of demos given. A sales manager checks the team's activity log to see if the new strategy is being executed as planned. These measures are not perfect, but they are better than nothing, and they give us something to work with when evaluating the effectiveness of a sales intervention.
For example, a sales team might implement a new AI-powered tool to help with lead qualification, and they might track the number of leads qualified per week as a leading measure of the tool's effectiveness. This measure is not the same as the ultimate outcome - revenue - but it is related, and it gives the team something to optimise as they refine their sales process.
Why aggregate outcome metrics move for unrelated reasons
Aggregate outcome metrics, such as total revenue or sales growth, are often influenced by factors outside of the sales team's control, such as changes in the market, the economy, or the competitive landscape. This means that even if a sales intervention appears to be effective, based on the aggregate metrics, it may be due to other factors, rather than the intervention itself. Most people get wrong that these metrics are a reliable way to measure the effectiveness of a sales intervention - they are wrong, because these metrics are too noisy.
A shift supervisor at a manufacturing company might notice that sales are up, but it could be due to a new product launch, rather than the sales intervention. To really understand what is going on, the supervisor needs to dig deeper, and look at more detailed metrics, such as sales by product, or sales by region.
The sales data this depends on
To really measure the effectiveness of a sales intervention, we need access to detailed sales data, including historical sales at the planning grain, order book and pipeline, inventory positions, and promotional calendar. This data is essential for understanding the context in which the sales intervention is taking place, and for identifying the specific factors that are driving the outcome. The category manager compares two suppliers based on their historical sales data, to see which one is more reliable.
For instance, a company might have a promotional calendar that shows when different products are on sale, and this information can be used to understand the impact of the promotion on sales. Similarly, the order book and pipeline can provide insight into the sales process, and help identify bottlenecks or areas for improvement.
What it changes about
A sales intervention can have a significant impact on the sales forecast, and on inventory levels. If the intervention is effective, it may lead to an increase in sales, which can result in inventory being out of step with demand. This can be a major problem, as it can lead to stockouts, or to excess inventory that needs to be written off. A forecast that nobody can interrogate is useless, because it does not provide any insight into what is driving the sales.
For example, a company might implement a new sales strategy that results in a significant increase in sales, but if the inventory levels are not adjusted accordingly, it can lead to stockouts, and lost sales. On the other hand, if the inventory levels are increased too much, it can lead to excess inventory, and waste.
Measured with
The effectiveness of a sales intervention can be measured using metrics such as forecast accuracy, win rate, and stock cover. These metrics provide insight into the sales process, and can help identify areas for improvement. A sales team might use sales team management software to track these metrics, and to refine their sales process.
For instance, a company might track the forecast accuracy, to see how well the sales team is able to predict sales. This metric can provide insight into the effectiveness of the sales intervention, and can help identify areas for improvement. If you want to know more about how to measure the effectiveness of a sales intervention, you can contact us for more information.
What this does not do
This approach to measuring the effectiveness of a sales intervention does not provide a complete picture of the sales process, and it does not take into account all of the factors that can influence sales. It is also limited by the quality of the data, and by the ability of the sales team to execute the intervention effectively. Most people think that this approach can be used to measure the effectiveness of any sales intervention - they are wrong, because it is only suitable for certain types of interventions.
Frequently asked questions
How can we measure the effectiveness of a sales intervention?
By tracking leading measures like meetings held and proposals submitted, and comparing sales by product or region.
Why are aggregate outcome metrics not reliable for measuring sales intervention effectiveness?
Because they are influenced by external factors like market changes and economic conditions.
What data is needed to measure the effectiveness of a sales intervention?
Detailed sales data including historical sales, order book, pipeline, inventory positions, and promotional calendar.
How can a sales team use metrics to refine their sales process?
By tracking metrics like forecast accuracy, win rate, and stock cover, and using sales team management software to identify areas for improvement.