From Data-driven Marketing to Artificial Intelligence
Think holistically at an early stage.
Marketing data is the fruit of your labor, because they give a lot of insight into how your website and your channels perform. If you are aiming for data-driven marketing, you have to be sure that the basis is right. This includes the quality of the data, how they are evaluated, as well as how they need to be handled if they come from different data sources.
In fact, the error rate is extremely high, which is why it is important to analyze continuously to discover potential sources of error. Unfortunately, however, data is often only viewed superficially and selectively. For example, during or after a campaign, when only specific key performance indicators (KPI’s) are pursued. Yet, a correct evaluation of data gives much more insights. At the same time, in-depth analyses enrich the knowledge across marketing teams. They also help closing knowledge gaps and facilitating campaign tests.
From this gap analysis, in turn, the right questions can be derived when data is merged, e.g., in a data warehouse, and used for modeling and visualization. Based on trustworthy data, knowing your pivotal questions for your predictive marketing and the right data infrastructure, appropriate machine learning models can be developed.
The road to data-driven Marketing is rocky
Data silos. Data silos everywhere
In fact, most marketing departments have different data silos that should ideally be merged in a meaningful way. Not doing so means not putting past and present activities in context. It also means less data analytics and evaluation options as well as risking comparing data that don’t really have the correct “data label”. It is crucial that you know, how data is measured at the source and if you can really bring them into context with other data. You want to find out who else needs what kind of data in your company, as well as to what they really mean to your business and customer journeys.
Equally, the visualization of specific key performance indicators in dashboards must be done automatically with the help of interface integrations (API’s). This way, you must have your data all in one data lake and can rely on real time updates.
Data evaluations that don’t make you smarter
Unfortunately, this happens more often than expected: data is useless if it has been tracked incorrectly, for example if analytics has not been set up correctly or has not been systematically structured and classified from the beginning. Emphasis needs to be placed on analyzing, questioning and testing. Don’t settle for data errors. They should not be the basis for important decisions or future predictive models.
Sometimes data is only picked from analytics and plugged into a report. This has nothing to do with analysis and it also doesn’t give you much insights. Go for deep dive analysis, if you are serious about data.
Equally important is the visualization and storytelling of data so that your stakeholders can follow you and support your decisions. Pay attention to a correct evaluation, a red thread and a meaningful graphic preparation that puts your message at the core of your overall message. The potential of your marketing data is huge. Use it!
Privacy. Everything gets so complicated. Or does it?
From 2022, third-party cookies may no longer be tracked. This refers to cookies such as having been used by Google, Facebook other ad giants to create user profiles. These data are particularly valuable for campaigns. In order for marketing departments to still be able to show good performance, reduce costs and increse revnue, it is all the more important to build up a good database now to manage without third party cookies. Those who have a plan B at an early stage will be in a better position.
Data. Data. How artificial intelligence comes into play
Analytics is correct, Google Ads, your code and your dataLayer. All cliffs are circumnavigated and working with data is normal for the Marketing team. But how do you share data within the compnay? How do you bring context to stakeholders who do not work in the Marketing business on a daily basis? And how can you ensure that all data are realtime and unbiased? What is your data strategy to create reliable forecasts about user or customer behaviour? With machine learning, you can model data in such a way that you gain future-oriented, meaningful insights.
Data dashboards are excellent visualizations that can, if designed with the right KPI’s for the right target group in mind, be a huge support in transparency and decision making. As with every transformation, it is important to have a plan that fits your purpose.
Make regular reporting a top task
Therefore, make reporting a top task. This is the only way to develop a real sense of how good your data are, what moves customers and users or where you need to optimize technically. In addition, you will always have a strong set of arguments for important conversations at hand. And you can make fact-based decisions.
homo digitalis offers you data audits and reports with clear recommendations
- Consulting on your marketing data needs and technical solutions
- Data Audits and clear recommendations
- In depth data analysis and clear recommendations
- Indiviual reports and presenatations tailored at specific target groups
- Data dashboard designs
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