Three stages towards data driven marketing decisions

Here in this post I write about the three stages we are seeing companies going trough towards data driven marketing decisions. Most organisations are in one of these stages and some are moving trough them fast.

The stages can roughly be categorised in

1. Non-data driven marketing and decisions
2. Awareness and transitioning phase
3. Data driven marketing decisions and experiments

Where a company is depends a lot on the industry, how important marketing is for the company and multiple other factors. E-commerce and online travel tends to be more in stage 2 and 3 where-as some more traditional industries are more in stage 1. Some industries can be very heterogenous. Financial services is a an example of an industry with companies in all different stages. Some of the smaller companies are in stage 3 running a very effective marketing machine. Some of the incumbents still doing things the way they have always been done.

Characteristic for the different phases.

Stage 1: Non-data driven marketing and decisions

In this phase the company is continuing to operate the way it has been operating before. Characteristics for this phase is:

• The company relies on agencies and uses metrics the agencies are providing them with. The company does not really have well defined KPI’s or its own independent source of data for of the KPI’s. The agency can pick out numbers to highlight its own performance.

The result here is that the company is reliant on the reports its given by the agency but cannot really verify them and cannot steer or control its own KPI’s. Decisions therefore are not really done on numbers but more on how things have been done before and more based on internal relationships and feelings.

Stage 2: Awareness and transitioning phase

The catalyst to start the move towards a data-driven approach usually comes from external business pressure. It can be that the profit margins are eroding or the industry is going trough change which puts pressure on the company. A new competitor might have entered the space which forces everyone to up their game.

The transition in our experience is fastest if at the same time new marketing directors are brought in. They are not used to the old ways of doing things, not bound to the old relationships and can question everything.

Characteristic for this phase is:

• Numbers are given more attention, however numbers are still looked at in isolation in every platform separately. This leads to double-counting conversions and other issues like misalignment. However the awareness of data and numbers start to be there. There are much more discussions around metrics and KPI’s.
• Some teams might still look at vanity-metrics and easy-to-fake-metrics like impressions, clicks etc. But there is anyways now more discussion about the numbers and data. Teams might still look at entirely different KPI’s, eg. social team looks at impressions and search-team at revenue generated.
• There is not yet a full helicopter view of all marketing channel performance and spend. The realisation that all teams need to work towards the same KPI’s starts to be there.
• In this phase also work towards improving the data-pipelines and infrastructure is done. For example Cognita Group went through connecting the marketing channels, analytics and CRM: https://www.windsor.ai/case-cognita-schools/

Some organisational tension might arise in this phase as teams that have not been measured before on numbers start to be measured. These teams or agencies naturally shun transparency. It is important to not let these tensions derail the process as it otherwise might hurt the entire organisation. Discussion about data and metrics is always good to have so that the company and teams can agree on the metrics they want to work with.

Stage 3: Data driven marketing decisions and growth experiments

Some e-commerce companies are in this phase and online travel. Every campaign is run as an experiment, it has an expected impact and it is being measured. Results are being measured and discussed.

Ebay is the company I have seen with the most advanced infrastructure and culture for testing and experiments. All campaigns and experiments are automatically created and measured. The audiences are automatically randomly selected. There is lots of discussion around the metrics, the results and the cause-impact relationships as there always is. But its centered around KPI’s, experiments data and results.

This phase is characterised by:

• The company has independent data-source for numbers and can control the metrics and KPI’s themselves.
• There is one view of the KPI’s, performance and spend
• Usually there starts to be expertise in-house that know both the business domain and the marketing data better than an external ever could.
• The company starts making their own experiments, analysing all numbers critically. At this stage the company usually starts to be critical of Google's numbers also:)

 Full article here: https://www.windsor.ai/3-stages-transition-data-driven-marketing/