7 Steps to Data Maturity in Marketing

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The collection and use of data is becoming increasingly important for companies as part of the digital transformation. However, it is not enough for the data to just be collected, it must also be be made usable. And it is precisely in this area that many companies have major problems. Therefore describes Data Maturity the maturity level of the data in the company. The better prepared your data is, i.e. the more "mature" your data basis is, the better you will be able to Marketing optimize and sustainably improve . We show you seven simple steps to Ensure successful data maturity in the company and to maintain them.

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First steps out of your data bubble

Data collection is already a hurdle for many companies. Which sources should you choose? How do you find the right balance between meaningful data enrichment and a flood of data that you will never be able to evaluate, let alone use?

One example: Many companies use the Social media data of your own channels to analyze your marketing success. This is important and correct, but can quickly lead to problems if only this data is used. Because within your own channels, a one-sided picture is often shown, which does not necessarily reflect reality.

A good and successful data collection also includes the Data outside own channels and your own bubble. Because how your brand is mentioned on the Internet can differ significantly from what is seen on your social media channels. This applies just as much to positive mentions as to negative ones.

So the sources of data collection should be well thought out and selected. Follow the principle "as many as necessary, as few as possible"to achieve better data maturity. After all, only the data that you can also use later is really valuable. At the same time, you should not rely on a data set that is too small and unrepresentative.

Essential steps to achieve data maturity in marketing
Collecting, filtering, analyzing and applying data properly is most important to achieve data maturity in marketing (Fig: blog.gramener.com)

From data acquisition to data analysis

Once the data is available, it must be made usable. Unfiltered and unsorted, you cannot gain any insights from the collected data. It is therefore a matter of analyze the data sets through weighting and filteringwhich you can use particularly well for your marketing.

So, using social media data as an example, this means that you filter, for example, by channels and mentions on which a particularly good and sustainable branding is operated. You can thus create contexts and Keywords filter out which ones promise a particularly high reputation and which ones elicit great reactions on the net, for example.

This gives your marketing the opportunity to react to individual trends in connection with your brand and thus improve the success of the brand in the long term.

Corporate Reputation: Minimize Crisis Management Effort

If you have a "mature" data set, then you are able to, Identify changes quickly and effectively. If your data changes significantly, you can directly analyze the causes and react.

So if a shitstorm is building up against your brand, you can identify it early and thus get risk and crisis management on the right track early on. Through clever Campaigns can even succeed in making the shitstorm useful for the company and thus take the wind out of the attackers' sails.

Without high data quality and a regular review and weighting of this data, these steps would hardly be possible at present.

Unite sales figures and company data with analysis

Now you have sufficient data available in the company to use it efficiently in marketing and thus to improve your Address customers in a targeted and appropriate manner. But that is not enough. Because it is also necessary to include the market and the reactions of the market.

This means that you should try in the company, Reconcile the analysis data with the business data. For example, if your brand was used by a large Influencer mentioned, this can have an impact on sales figures. So try to overlay the data and its focus with the company's key figures to get an overview of how the key figures influence each other.

A good example in this case is the company Tesla with its founder Elon Musk. The various tweets of the company founder on the social network Twitter can be very well related to the development of the share prices and the sales and sales figures of Tesla.

Capture synergies and interrelationships

Based on this data overlay, the data maturity for your marketing can be improved again. The next steps are about the Targeted analysis and optimization. If you can identify which mentions of the company on which channels have a particularly high impact on your sales figures, you can use this specifically for your marketing.

So you are no longer exposed to random mentions and therefore fluctuations, but can be active with your marketing on the selected channels and with the corresponding actors.

Adapt and optimize marketing processes

For your company, however, this also means that you have to change or adapt many traditional marketing processes. Thanks to the data maturity in your company, new tools and new possibilities are open to you to make marketing much more efficient. closer to the target group and thus boost sales in the long term.

It is important that the processes used so far are not simply thrown overboard, but that you analyze the individual processes and check their effectiveness and functionality. Because processes that have been successful up to now are welcome to remain integrated, but are often improved and more strongly underpinned by the data quality gained.

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Recognize data maturity as an ongoing process and implement it permanently

Data maturity in a company is not a state that persists forever once it has been triggered. For this reason, it is important for companies not only to repeat the steps mentioned above once, but also to implement them in the future. Integrate into daily work and general company processes. This is the only way to ensure that you can use Big Data effectively and pull the most relevant information from these data sets thanks to Data Maturity.

This is a big change for the whole company and your work in marketing, but a necessary and important change. Because only in this way can you with your company remain sustainably efficient and optimally place your brand and your brand message.



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