Last month on our revenue marketing journey, we discussed how to develop use cases as a way of teasing out specific technology requirements for marketing. This month, we turn our attention to revenue marketing analytics and, more importantly, how to choose the right metrics for where you are in your revenue marketing journey.
Here’s a trap many marketers fall into in the early part of the journey: The marketing VP received additional marketing budget, but the price is that she has to report marketing numbers to the CEO each month. So the organization is turned upside down attempting to create marketing results reports for the first time.
How do they start? Marketing ROI analysis, or marketing influenced revenue, or, harder still, predictive reports? The outcome is predictable.
6 Steps to Accurate Revenue Marketing Analytics
If you are in the lead generation stage of your Revenue Marketing journey, moving into demand generation, and recently acquired marketing automation technology, here are your best bets for initiating revenue marketing reporting this year:
1. Avoid Ego Metrics for 6 Months
Marketing ROI and marketing influenced revenue. These require a lot of pieces to be in place and working and are simply not a good place to start. We recognize that they are important, but don’t try to start here. Avoid creating the ego metrics the first six months.
2. Define the Decisions
Start by defining what decisions the demand generation and content teams are making weekly and monthly and asking what reporting related information they need to make better investment decisions. Create those reports for them first. Good examples are:
- Weekly database engagement by campaign, content, channel, region, product interest, and contact type. Are they a prospect or a customer? Engagement means they downloaded or clicked on an offer, registered for something or visited one of your digital properties. It also includes engagement on the social channels (likes, replies, forwards, clicks). It does NOT include email opens.
- Form completion rates (or the converse, form abandonment rates).
- Net new leads by region, product interest, lead source and content/asset that attracted them.
- MQLs and SQLs by lead source, region and product interest.
- Cost per MQL from inbound sources.
- Funnel conversion rates, by contact type, region and product interest.
- Funnel age in stage (qualitative measure of the funnel), by region and product interest.
3. Fix the Errors
Reports like these will reveal all sorts of issues with your data and with the processes that update your data. You will spend months fixing these process issues and amending the data. You will probably also find that your data has serious omissions precluding you from reporting the way you want and a data enrichment project may be initiated.
4. Take Your Time, Before Sharing
Do not share the initial reports throughout the organization because it is likely that they are wrong. There will be errors from simply not having enough good data to be a representative sample to incorrect data to faulty report configuration.
If you share the early reports widely and the errors are uncovered by the recipients, it may take a while to recover your credibility. Take your time, validate your early reporting and gradually start to share them more broadly.
5. Are the Initial Reports Helping?
Sit in with the demand gen teams and content teams and see how they are using these initial reports. Are they useful for making decisions on a weekly or monthly basis? I.e. is the reporting cadence aligned with the required decision-making cadence? Are they getting the detail they need? Is there drill down required?
Modify your reports to fully satisfy this audience before you move to the next audience.