This is the ninth article in our 12-part subscription sales series, designed to help you understand and prepare for the evolving sales landscape. This article expands on our previous piece on building a data foundation and demonstrates how to correctly leverage your data to drive better business decisions. Don’t forget to read the previous eight articles in this series; a new sales strategy, customer segmentation, understanding your customer market, customer-centric sales approaches, understanding the customer journey, the road to profitability, online channels and part one of our data guide.
Before continuing with this post, we recommend you read our previous article, A Guide to Data Part 1, as it details the foundations required to be established before a business can consider data reporting.
Once the foundations of data processes and quality are in place, organisations can progress towards leveraging data to drive better long-term sales performance. The final layer requires an understanding of what businesses should measure and report, and how.
Measuring and forecasting performance
Most organisations are still measuring data snapshots. More advanced businesses manage to sporadically input pipeline data into their CRM to review the volume and value of leads at each stage of the sales journey. Some companies still use their performance from last quarter, add a nominal amount and then consider this figure to be the forecast for the next quarter.
Using data effectively means measuring data flows, not snapshots. Data flows are ratios. They can provide value insights, such as the ratio of Dave’s monthly recurring revenue to sales qualified leads, or Sally’s ratio of committed sales to sales qualified leads. These ratios can demonstrate whether a business needs more employees like Dave, or whether Sally’s sales behaviours should be replicated. To become a truly data-enabled organisation, ratios need to be frequently monitored in increments of weekly, daily and even hourly.
There are a wealth of ratios that organisations can use for reporting. At a minimum, we recommend sales organisations measure the raw number of Suspects, Marketing Qualified Leads, Sales Qualified Leads, Committed Sales, Live Accounts and Monthly Recurring Revenue.
Measuring this data shows where the business is at for any given tier. It can demonstrate that Dave is generating more SQLs and MQLs than Sally, and that they should therefore hire more people like Dave. It can also show the amount of inbound leads and their cost, plus the number of outbound leads and their cost. Comparing the two confirms which sales strategy is more profitable.
For multi-tiered organisations, it is important that numbers and ratios are reported separately for each tier, because the cycles and sizes of larger customer tiers will mask those of smaller tiers. We also recommend reporting by individual and team pipelines, as conversion rates and volumes can vary substantially.
Types of data
There are three categories that give an organisation a view of performance across sales pipelines. These are:
- Volume data: tracking volume by counting events such as MQLs, SQLs and WINs.
- Conversion data: ratios between measurement points e.g. MQLS, SQLs and conversation rates.
- Performance data: extrapolating multiple measurements points. Examples include measuring MRR generated by a single marketing campaign in 30 days, the length of a sales cycle, upsell percentages, or the client acquisition cost of the online team versus the field team.
There are numerous ratios an organisation can use as their data point. A data analyst is responsible for confirming which ratios a business should focus on. Importantly, a data analyst is not hired to fix business processes and data accuracy. This must be addressed before a data analyst is onboarded.
It is counterproductive for a data analyst to work with assumptions or need to fill gaps in data. It is not the data analyst’s responsibility to create or implement data processes. Their sole purpose is to leverage good data to build meaningful reports and provide business insights.
Marketing teams that have been leveraging data for years demonstrate that the data analyst role is increasingly prevalent. The entire makeup of sales teams is shifting. Future sales will comprise multi-functional teams that create content, develop leads, analyse data and solve customer problems long after the solution is delivered. Sales will become the microcosm of entire businesses.
Contact us for more information on leveraging your data to improve your long-term performance.
Next in this series we explore subscription sales processes.