There are some public sources that give you quite some interesting metrics specifically for Saas companies like Bessemer Venture Partners, David Skok and KISS metrics. What I have learned over the past 5 years at Exact is that it is a hell of a job to get everything right from theory, to a blueprint, a working model, execution and a dashboard. One of the key things is to stick to the definitions that you have once created in collaboration with Sales and Business Control. This is the only way to create one truth that everybody is looking at. I my previous blog posts I already shared our customer buying journey blueprint with all definitions in there:
All what is stated in the model above is measured across 7 countries for 5 different target audiences in one consistent way. Some of the main marketing metrics and KPIs we measure:
- MQi = #visitors on a landing page
- MQL = #contacts who did a content download
- SAL = sales accepted leads in 7 different types
- SQL = sales qualified leads
- Sales Conversion % = conversion % from SQL to a customer
- Cost Per SQL = marketing spend/#SQLs
- Cost Per Acquisition = (#SQLs required to generate one customer) x CPL
- ROI = payback time in months
We have many more but these you can consider as our main metrics. In the systems that we use to run our marketing programs all this data is stored. At the same time this is our main challenge: get the data out of these systems in order to create one consistent view. Our data is stored in our financial system Exact Synergy, our CRM system Exact Online, our marketing automation system Oracle Eloqua, Google Analytics and Google DoubleClick. Recently we started to use Microsoft PowerBI to gather all data and create some valuable marketing dashboards. This really accelerated the quality of discussion we have within marketing but also with sales. In 2016 we passed the magical number of 300.000 companies who are on our digital business platformEasy accessible insights do make the data more actionable. E.g. one of the key topics for 2017 is improving the quality of the SQLs. This we can do by analyzing all SQL data and see which lead types convert te best. Signing up for a trial is one of our lead types and converts way better than for instance our ‘online demo‘. What we also see is that once contacts have seen a message (e.g. video, display advert) to generate MQLs are retargetted with a SQL message and than convert into a trial, have in some cases double the sales conversion % of a ‘normal’ trial SQL. That all sounds logical but to get the proof based on data is a major job.
Example of a so-called MQL message for the wholesale target audience
Specific marketing KPIs
Ok, now I have showed you some of our key marketing metrics lets get more specific. All given numbers are across all 7 countries across all 5 target audiences in 2016. Off course I have even more specifics along those 2 dimensions but I think this is ok for a start.
- 58.000 = #SALs we generated
- 29% = our average sales conversion %
- € 208 = our average Cost Per Lead
- SQL = sales qualified leads
- 5 months = our average payback time for every marketing Euro we invest
There are substantial variances between the different countries and the different products. The number of SALs we are generating is based on the growth in add MRR we want to achieve. In order to calculate the marketing SAL target we take the actual sales conversion % of the previous year and add a certain optimization %. Combined with am actual CPL we know exactly what to spend in order to generate the required growth.
In 2016 we were able to grow our revenue with almost 40% compared with 2015. In our international countries we were even able to grow more than 90%!
Different countries, different numbers
Once we dive further into our SQL data we gain some interesting insights. As mentioned earlier we consider 7 different lead types and each and every type in combination with a country and a product has their own dynamics. Our programs aimed at manufacturers show better traction traditional lead types e.g. telemarketing whereas the more tech savvy professional services industry shows better traction on our trial lead types.
- About 38% of all our SQLs are trials
- Only 8% of our SQLs are generated through telemarketing
- 15% of all the SQLs generated are for the professional services industry
In orde to improve the quality of the SQLs we closely monitor the mix of lead types that we generate. We would rather go for high converting trials than for low converting online demo’s.
- Our inbound lead type converts more than twice as good than trials
- Online demo’s and webinars are the SQLs with the lowest sales conversion %
- Accountants show the highest % of event lead types, about 15%
We also see big differences between the countries in all metrics. Cloud adoption is a key driver for this but also cultural aspects come into play. Companies in Germany by nature are more risk averse than for instance the UK. Generate SQLs in the UK costs us the most whereas in Belgium we see the lowest CPL values. UK is a highly competitive market that is still seen as a step-up towards mainland Europe. Many US competitors start in the UK and that drives cost-per-clicks within Google upwards. We also see that the % of UK website visitors that apply an online form with invalid data is almost double than for instance Spanish website visitors.
Hereby I challenge my peers to also share some specific marketing metrics to reflect with each other
All in all many many metrics that we can look into in order to further improve our demand generation engine. In 2016 we passed the magical number of 300.000 companies who are on our digital business platform. We add new companies each and every week and that number increased with about 40%. Right now we add 1.400 new companies to our platform each week! And this is how Saas in an upcoming market is being monitored and measured by the growth of the growth. Time to get exponential 😉