This installment of our Data Driven Marketing Strategy Development Tips is about the bottom rung of the Data Survival Pyramid, the foundation. It's about data access and sourcing. Our text provides some background, but above all four concrete recommendations for action, what companies should do to gain decisive advantages in marketing and communication with the help of data.
In the oil business, to use the well-known metaphor that also vividly explains mechanisms of the data business, the beginning of value creation is about exploring new sources, developing them, and producing oil (data).
At the beginning of the value chain, it makes no difference whether the oil (the data) is used to produce gasoline or chemicals. And likewise, for the marketing and communications data, it does not yet make a difference whether I want to use it for optimizing content, image advertising or direct marketing. All the data (oil) listed below must be secured for the company. Because they have a value - in any case.
If you want to create value from data, you have to have access to the data. This connection is so logical that it almost sounds silly to mention it. And yet it is always surprising how little attention is paid to companies' rights to their own communications data. In this context, marketers who do not claim processing rights for their own data will not have a successful future. It's also amazing how much resistance agencies put up when it comes to exporting data generated with companies' money.
But first things first. Here are the four key questions and answers about sourcing the data that any "Data Driven Marketing" needs outside of silos.
First of all, what is the Survival Pyramid?
Our survival pyramid is a layered model for developing data-driven value in communications and marketing departments.
As a strategy tool, the very name of the model fulfills an essential requirement for any strategy process: every strategy must have a goal. Our goal is to ensure the continued existence of the organization under digitization conditions. We therefore understand "survival" entirely in the sense of evolutionary theory.
Question 1: Why should companies develop a data strategy for marketing and communication at all?
1st answer: Because they can draw long-term and lasting competitive advantages from data.
The simplest and most immediate motivation for a data strategy is that most social media and advertising platform performance data is usually no longer accessible after a few months. Therefore, for longer-term use, they must be stored on other systems that the company controls. The most important motivation to actually do this is this: unlike agencies, companies can permanently link media performance data (KPI) with impact data (KPI).
The impact KPIs usually come from sales or service channels. However, they can also be data from continuous brand measurement (surveys) or data from continuous media monitoring (resonance). This already names all possible impact levels of marketing communication. There are exactly three: 1. sales, 2. brand, 3. media response.
If we succeed in linking performance data (media data from owned, paid, social) with the above-mentioned impact data, we are no longer talking about tactical KPIs for specialists, such as media planners, but about easily understandable and highly relevant efficiency KPIs for management and division heads. A cost per order (CpO) or cost per branding of 23.10 euros is an example of this. At this altitude, you can catch any CMO; below that, at the detailed levels of an evaluation, the same data becomes a specialist topic.
Agencies also deliver a CpO, but is it comparable to what other agencies deliver? And can it be correlated with changes in any of the other four Ps in marketing (Price, Placement, Product)? At this point, the additional potentials for data-based value creation that only companies have begin. They end in simulation, predictive planning and automation.
Question 2: What data do companies need for "Data Driven Marketing"?
2nd answer: The essential performance and impact data from all digital sources.
Companies that want to implement "Data Driven Marketing" (not: experts who want to control silos!) need:
Owned media performance data (website or app)
- Content and campaign identifiers for marking and measuring own outputs
- Impressions per output
- Engagements per output
- Cookie-based data, e.g. on users and so-called "customer journeys" or "attributions" (this does not apply to services with log-in), is already superfluous and, at the latest with the e-privacy regulation, also illegal.
Owned media active data (website or app)
- Identifier for marking and measuring clicks on target actions
- Identifier for marking and measuring users or customers (only in case of consent or log-in)
- if own sales or service channel: extensive further data from the sales process
Social media performance data (organic and paid, all platforms)
- Content and campaign identifiers for marking and measuring own outputs
- Impressions per output
- Engagements per output (also video engagement data)
- useless outside silos because not aggregable: unique users
Social media impact data (outcome)
- if own sales or service channel: extensive further data from the sales process
Paid media performance data (display, video, search, native advertising, all platforms)
- as above
Paid media impact data (outcome)
- Ad clicks
Earned media impact data
(resonance data from media and social media monitoring)
- Mentions
- Engagements
- Sentiment
- Useless: the range data "cubed" differently by all tools (to be recognized by astronomical dimensions)
Brand impact data (attitude and image data, collected through surveys)
- Can only be used for "Data Driven" in exceptional cases, as sufficiently frequent surveys are usually only available for branded companies in the FMCG environment (fast-moving consumer goods).
- KPI: depending on survey methodology
Sales impact data (collected in website, app, or in other sales and CRM systems such as SAP)
- KPI depending on business model and marketing strategy: statements on number of sales, new customers, regular customers, etc.
3rd question: What do companies need to do to gain sovereignty over their data?
Response 3: Identify the relevant data sources and enforce access and export rights for non-aggregated data with all internal and external stakeholders.
No one from whom you request export rights wants to become controllable and comparable as a result. So at best, expect restraint from colleagues, other departments or agencies.
Determination and good communication are important to overcome such resistance. If other departments in the company block a solution, it can often only be found from the top down - by issuing instructions. It is only a matter of time before such an instruction is issued internally; the potential that opens up once a "data lake" has been created is too great.
And yes, any agency, even media agency, will sooner or later grant export rights to any company. At the latest when, we strongly recommend, the rights to non-aggregated export of media performance data generated with their own money are made a contractual requirement in the next agency pitch.
Question 4: What must the relevant department do to gain sovereignty over its data?
4th Answer: Rebuild and centralize your processes to generate the right contextual data.
Context data - what is this about? We are talking about the "identifiers" from point 2, they are very diverse. They can be campaign IDs, embedded link IDs, tracking pixels, hashtags, SEO metadata, content tags from internal and external publication systems - in all cases, they are expert topics, even nerd topics, that need to be unified and organized in a coordinated workflow. Either way, it's complex and you get the idea: HERE lies the biggest challenge for companies embarking on the journey to "Data Driven". It's about reorganizing workflows and digital governance that needs to be aligned and enforced. In distributed and large organizations, this requires significant investments in tools and management systems. We are happy to advise.
You can read about how Data Driven Strategy starts and what is critical at the lowest level of data sourcing in the next "Datafy".