I recently came across an article in Marketing Week regarding the position of the CMO in organizations. It gives food for thought.
According to the described study, in none of the FTSE 100 companies is there a person performing the traditional function of CMO or marketing director on the main board of the company. In 2007, marketing had its representation there in 14% of companies.
This does not mean that marketing has disappeared from the most important decisions. The authors of the study indicate that 70% of these companies have marketing, client, or brand competencies at the board or senior management level. Roles and responsibility structures are changing.
For me, however, this is a signal that should not be ignored. Marketing must know how to show how it helps the company grow and earn.
The campaign generated leads. What happened next?
We report website traffic, reach, clicks, leads, and the cost of acquiring them. And then comes the conversation with the board:
How much sales do we have from this? What revenue? What margin? Is this investment paying off?
And right here, answers are often lacking.
In automotive, this problem is clearly visible. The campaign generated sales leads. But what happened next?
Did the dealer contact the client? Was an offer created? Did we sell the car? With what margin? Did the client return to the service department later?
Without connecting this information, it is difficult to assess the real value of marketing activities.
A cheaper lead does not have to mean a more profitable sale. A good ROAS also doesn’t answer the question of how much the company earned after accounting for margin and costs.
What’s more, the problem may lie in handling inquiries. We increase the budget, generate more leads, and some customers still do not receive a response on time. Without data on further sales stages, it is hard to decide what to improve first.
Marketing must speak the language of business
In my opinion, the CMO and marketing must speak the language of sales, revenue, margin, profit, market share, and return on investment.
Except that changing the language alone is not enough. You need access to data that will allow you to hold such a conversation.
Marketing has its reports. Sales works in the CRM. The dealer has the DMS, and finance has further statements. Everyone sees their own fragment.
It is difficult to put together a shared picture from this and show where value is created and where we are losing opportunities.
Added to this are different definitions. What do we consider a lead (MQL vs SQL)? When do we count a sale – upon order or car delivery? How do we attribute a transaction to an earlier inquiry?
If everyone counts differently, even correct reports can lead to different conclusions.
This is the direction we are developing Datadise in
We want to help importers and dealer groups answer questions that matter to their bottom line.
Automotive Intelligence Platform combines the necessary data from marketing, websites, CRM, DMS, service, market, and finance. We can start with one business priority and expand the solution to further areas.
Automotive Golden Context gives this data a shared meaning. It allows connecting information about the client, their inquiry, sales activities, and transaction, as well as organizing definitions and measurement rules.
Thanks to this, we can help answer specific questions:
- Which lead sources result in the most profitable sales?
- Where are we losing customers between lead and purchase?
- Will an additional budget or an improvement in lead handling bring a greater effect?
- Which clients return to the service department and what value does this relationship bring?
Simply linking an ad to a transaction does not yet prove that the ad caused the purchase – that requires an additional evaluation of the effect. But without connected data, it is difficult to even start this conversation.
This is the essence of our Datadise 3.0 direction. We combine data and add business context so that better decisions can be made based on it.
Let’s start with one question
You don’t have to start with the entire data environment. We can start with one question that is hard to answer today.
For example: which lead sources result in the most profitable sales?
We work according to our framework Measure → Connect → Improve:
- Measure: we determine what we want to improve, how to measure it, and what the starting point is.
- Connect: we connect the necessary data and agree on their definitions.
- Improve: we use this information for action and check the effect.
Then the conversation about marketing can go beyond the number of leads and the cost of acquiring them. We can talk about what brings sales, where we are losing margin, and what is worth changing.
How does it look for you? Which question about marketing results is the hardest to answer today?
