To improve any business, you have to measure and manage using Key Performance Indicators (KPIs) and metrics. But, to meet your strategic objectives you may also need validation metrics and learning loops.
KPIs measure change in your strategic objectives. You should choose other metrics to help you,
This example of KPIs, metrics, validation metrics, and learning loops will use a marketing and sales funnel.
In any organization there are some who will “game the system” – they manipulate the process or KPIs and metrics to make their unit look successful.
They may be driven by conscious ego-political motives, disagreement with current strategy, or unintentional selection bias. Whatever their reason for cheating or lying, an organization cannot succeed or be sustainable if it makes decisions on false data. To prevent this, you need to add a validation metric to some KPIs.
I have seen an entire division go down and a thousand people lose their jobs because a division’s management seemingly allowed manipulated sales numbers. Organizations may win by cheating in the short term, but they eventually collapse from the lies, crushing both innocent and guilty.
What can you do in your business to pick the right KPIs and metrics so they aid business improvement and also prevent or reduce manipulating data?
Before discussing KPIs and metrics, it’s good to define what they are. Sometimes they are misused.
A metric is a quantifiable measure of a business process or performance. Metrics are often used to measure operational performance.
A Key Performance Indicator (KPI) is a metric that is critical to the success of the business. A KPI is used to measure change in the strategic objectives of a company or business unit.
It’s not uncommon for organizations to have hundreds of metrics. But, out of all of those metrics there might be as few as three to five KPIs measuring the impact of strategy at the highest level. Each business unit will also have their own set of KPIs specific to each unit’s objectives. A business units KPIs should have a direct causal link, be a driver, or the organization’s KPIs.
Metrics are the operational measures that support or drive KPIs. While KPIs measure success in achieving the organization’s objectives, the metrics measure the operational processes that drive KPIs.
Only a Few Metrics Are Critical, Pick them Wisely!
Have you ever looked at a jet pilot’s dashboard? There are hundreds of dials, gauges, and readouts. But, it only takes four (4) to really fly a plane.
All the other instruments in the cockpit are there for communication, maintenance, troubleshooting, etc. But, they aren’t necessary for flying in the moment.
One way to prevent gaming or cheating with KPIs and metrics is to use a validation metric. The validation metric acts like a fire-alarm and should alert everyone when the primary KPIs and metrics might not be valid.
The easiest way to illustrate this is with an example I’ve seen in a few businesses. It involves the customer funnel, from first contact with a customer to final sale. This example uses validation metrics to catch cheating as well as a couple of “learning loops” that give feedback and produce continuous improvement.
A customer funnel starts with a customer’s first contact with marketing and continues through sales. One of marketing’s primary objectives is to generate quality leads and pass them to sales. The primary objective of sales is to close those leads and generate revenue.
There are specific points in the journey from first contact with the customer (first attribution) to final sale that are good points for measuring performance. Some points also measure how well marketing and sales work together.
From left to right, this table shows a customer’s journey from the top of funnel (TOFU) through to sale. (A good customer funnel would continue through the customer support and recapture stages.)
Some of terms used are,
TOFU is the top of the marketing funnel. This is the first contact point with the customer.
MOFU is the middle of the marketing funnel where a customer is informed, nurtured, and persuaded.
BOFU is the bottom of the marketing funnel where a customer is making product comparisons, deciding on features, and almost ready to make the purchase decision.
A Marketing Qualified Lead (MQL) is a lead that has been reviewed by marketing and has high potential for becoming a sale. Marketing wants to pass MQLs to sales.
A Sales Accepted Lead (SAL) is an MQL that has been reviewed by a sales development rep and approved for the sales team to work with. Sales development doesn’t want to waste time, so it wants to only accept leads from marketing that are well qualified.
A Sales Qualified Lead (SQL) is an SAL that has been tested by sales development to insure it has Budget, Authority, Need, and Timeliness (BANT) to make a purchase. (There are other terms than BANT for qualifying leads.) These are leads that should be sent to sales reps to close.
In this example there are six KPIs, but these six span marketing, sales, and strategic objectives. The other metrics are there as validations or for process improvement.
Sales and marketing might feed into only two Strategic Objective KPIs, Revenue and Average Revenue per Sale. (These could be different KPIs for Sales if the strategy is different.)
This figure shows the first column of the table (labels) and the last column (Sale), to show the two strategic objectives $ Revenue and Avg Revenue per Sale.
Strategic Objective KPIs
$ Revenue measures all sales for this channel, target, and strategy.
Average Revenue per Sale can be an important measure of how well the sales force aligns with the company’s strategy on target markets and expansion.
In this example, marketing has a minimal set of two KPIs and one validation metric. In this company marketing is being measured on quantity and quality of leads.
# Contacts is a KPI that shows how effective marketing is at attracting a growing quantity of contacts.
% MQL/TOFU is a KPI that measures the quality of contacts marketing is attracting. This is the percentage of contacts from the top of funnel that turn into Marketing Qualified Leads.
Marketing Validation Metric
% SAL/MQL is a validation metric of marketing’s quality of lead and how well marketing and sales work together to identify and qualify leads. Marketing and sales must work together to identify what makes a Marketing Qualified Lead (MQL) and Sales Accepted Lead (SAL). If this percentage is low, then there is a mismatch between what marketing and sales think are quality leads. (You might also use % SAL/TOFU as a measure of quality of attractiveness.
Sales has two KPIs, Revenue and Average Revenue per Sale, used directly as strategic objectives. It also has a KPI to measure its percentage of sales from qualified lead, % Close/SQL, and a metric to validate that KPI, Margin on Sale. It also has a few validation metrics.
Revenue measures total sales.
Average Revenue per Sale can be an important measure of how well the sales force aligns with the company’s sale size which could be important to corporate strategies of the correct target markets and expansion.
This is the percentage of sales closed out of the qualified leads.
Sales Validation Metric
Margin on Sales
Margin on Sales is a validation metric that insures the sales force doesn’t increase their revenue by cutting margins. I have seen companies make revenue targets but continue to have serious financial shortfalls because they allowed serious cuts in margin.
The learning loop data, in the last row, can improve performance. This may not be quantitative data. It may be survey or interview feedback. For example, Reasons for Disqualification underneath Marketing Qualified Lead could show that marketing campaigns are attracting the wrong audience.
Learning Loop Metrics
Marketing MQL: Reasons for Disqualification
Optimizing marketing to attract high-quality leads is far more important than attracting high volumes of leads. In one large digital campaign for a rapidly growing tech company I saw huge numbers of online visitors come in from a campaign, but there was not a single qualified lead. All the visitors came from organic searches (typed into a search engine) looking for information on “Steven Covey’s 7 Habits.” They had no interest in the product.
The title of the campaign’s webinar included the phrase “Steven Covey’s 7 Habits.” What happened was that a large audience was attracted by the phrase “7 Habits” but they had no interest in the product.
Sales SAL: Reason for Non-Acceptance
Reason for Non-Acceptance is another learning loop metric that builds a learning loop between sales and marketing. A few simple comments on why an MQL was turned down by the sales development rep can help marketing fine-tune their campaigns and persona.
Having a list of Reasons for Non-Acceptance makes for good conversation starters between marketing and sales!
Sales SQL: Reason for No Contact
Reason for No Contact is effective when marketing sends more leads to sales than Sales Development Reps can call and qualify. A Reason for No Contact list can show that non-contacted leads are not low quality leads from marketing, but that Sales Development needs additional staffing to qualify more sales opportunities.
Analyze Text Comments with Excel to Create a Learning Loop and Optimize Lead Generation
In Excel you can analyze text comments and create a table of how many comments contain specific text terms. To do this, scan text comments in your CRM and create a list of frequent terms, such as “no budget”. Export comments from your CRM to a CSV file which is then imported into Excel. In Excel, create one column for each text term you found in your manual scan. Use the term as a column header. For example, “no budget” might be the label of one column. Now fill each column with a FIND() function that search the exported comments for the term in the header. This will give you a table showing which Reasons for Non-Acceptance occur most frequently.
KPIs and metrics are absolutely essential, but when you define them, spend a little more time thinking about what metrics can validate your data so it won’t be “gamed.” Also, consider what data will create a “learning loop.”