If you know the real story of the first man to successfully circumnavigate the earth, you know that Ferdinand Magellan died 16 months before his mission was completed. Despite his devastating death while in battle in the Philippines, his crew fearlessly sailed on without him – and completed his quest.
They succeeded because Captain Magellan took the time to put the right KPIs in place – and his leadership team was deeply involved in the management, course predictions, and execution of the mission. Since they knew the predictable trajectory and the foreseeable obstacles before them, they were confident in carrying on to the finish line without their leader.
As a CMO, I consider it my duty to provide navigable guidelines for those who are wondering what the best business growth metrics are for tracking, measurement, and forecasting. While Magellan’s guys didn’t exactly employ the same metrics as the ones I’m about to show you, it will be a good start in confidently sailing the challenging seas of your business marketplace.
Here are some recommended data sets that should up your game in projecting the performance of your business. As we discussed in the last article, keep in mind that you know the pressure points of your company a lot better than I do. While this will provide a great start, consider adding another metric if something seems awkwardly missing.
Depending on the complexity of your industry, you’ll likely have subcategories in the Sales Revenue metric bucket. For certain, you want to understand the overall movement and trajectory, but there are a number of factors that can affect your sale revenue picture. Refer to my earlier example for an illustration.
I generally recommend tracking data points that not only show the big rollup of sales revenue, but also reveal how key products are performing, as well as what the picture looks like for new and existing customers. The “devil’s in the details,” as they say, and so is the path to the Holy Land.
Dig in and make certain you understand your sales revenue picture. Doing so will give you a lot more confidence in understanding where you are and in forecasting the future based on reality, not wishful thinking.
Ditto everything I said above, with a critical eye on how well your sales are growing. What is the glaring trend (or trends) – and what does that mean for the future? How does today’s growth look versus your numbers this time last year? How about in comparison to your annual sales plan? Assuming no major seasonality spikes are coming, if 52 percent of the year has passed, sales revenues should be higher than 52 percent to reasonably predict making the plan. Remember, the higher the better.
The difference between an MQL and an SQL is essentially in the eye of the beholder. Every single lead generated by the marketing engine won’t become a qualified sales prospect. Some are tire kickers, while others are genuinely interested shoppers. If the prospect has achieved the established marketing criteria for lead acceptance, it will be classified as an MQL.
Make sure your marketing team has distinct and well understood reasons for qualifying leads – and track them as a subset of inbound leads generated through the marketing funnel. MQLs always get passed on to sales. Much to the chagrin of your marketing leader, all MQLs are not going to become Sales Qualified Leads.
Based on the profile of the lead, thumbnail research, or the information documented in your CRM software, your sales team should be able to quickly identify whether or not this is a genuine prospect. A vetting step is needed before simply converting an MQL into an SQL. For example, a new inbound lead from a recent prospective client marked as “closed lost” just three weeks ago is probably not a Sales Qualified Lead today.
Another example might be an MQL in the form of a low level person who has no influence or impact on decision-making or the buying process. That lead is unlikely to pass the sales litmus test and become sales qualified. Regardless, track your MQLs and SQLs in a month-to-date and year-to-date fashion. From a predictive standpoint, I’d recommend comparing them to growth goals on a monthly, quarterly, and yearly basis. Looking back at data from past years can be helpful, too.
“Lead to Client Conversion Rate” is a fancy way of showing you’ve figured out what percentage of SQLs and MQLs end up as closed deals. With an established trend, you can essentially predict the trajectory of your Lead to Client Conversion Rates.
For example, if 10 MQLs are handed off to sales, and two end up as closed deals (converting from a prospect to a client), the predictable close rate is 20 percent. If 1 in 10 SQLs end up closing, the SQL client conversion rate is 10 percent. Over time, you’ll get more comfortable with a predictive trend percentage and seek ways to improve it.
This is a very important metric from both a marketing and sales perspective – and it can really help you forecast the effectiveness of each team. It’s all about closing deals and generating revenue, not to mention predicting how well your business will perform in the coming months, right?
In the final article of the series, we will uncover the last of the four key predictive indicators for forecasting your growth trajectory – and alas, you will be ready to set sail. For now, examine the first few KPIs and start considering if you need to add more.