Create your very own Auto Publish News/Blog Site and Earn Passive Income in Just 4 Easy Steps
https://www.youtube.com/watch?v=pf5arphieuq
Marketing experts were sold a dream: collect more data and you will receive better findings to make more intelligent decisions.
We all followed Big Data, accepted the digital transformation and invested in AI-operated analyzes, hoping that the difficult to meal 360-degree view of every customer would finally occur.
As it turns out, the persecution of this perfect customer view is very much like chase. Many people swear that they saw it but have no evidence. Usually it turns out that the reality are blurred images that seem to have been absorbed by a potato.
But most of the marketers drown into numbers and hunger for insight. Despite endless reports, dashboards and attribution models, marketing teams have difficulty answering basic questions, including:
- What value does content marketing offer?
- What promotes conversions?
- Which customers are shortly before the emigration?
- Do we spend our budgets in the right places?
- How do we implement a personalization strategy?
Instead of clarity, we received data silos, contradictory metrics and an overwhelming flood of numbers that rarely complement a meaningful picture.
Further data have not solved any problems in marketing – it only made it bigger.
Take a look at the video above, read the rest of this article or register to download this research paper to find out what your data challenges will solve (and not).
Other dashboards are not the answer
You will probably collect more data than ever. And you are not alone. The average enterprise marketing team collects findings from 10 or more different data source CRM systems, web analyzes, marketing automation platforms, social media monitoring tools and now AI-controlled personalization engines.
The result? 67% of the CMOs state that they feel overwhelmed by the mere volume of the marketing data. And this is because most teams are not equipped to understand everything.
The real problem was never enough data. The problem is the inability to standardize, contextualize all of this data.
For years, companies have tried to fix the data problem by throwing the technology on it. You tried:
- Better dashboards – But more graphics no longer mean clarity.
- Other AI-powered analyzes -Bich even the best algorithms can repair non -separate data with low quality.
- New attribution models – But map customer behavior with faulty data leads to incorrect knowledge.
What is missing is not another analysis tool – it is a strategic approach (i.e. a way to make marketing data implementable).
Enter a uniform data strategy
The answer is no longer data. It is a better approach to data.
A uniform data strategy (UDS) is not just another acronym or a keyword – it is a rethinking how marketing teams use data. A UDS prioritizes the data co -esion for data acquisition, the context over volume and the ability to act rustlates.
A UDS prioritized:
- Data integration Use marketing, sales and customer success data in a single, structured ecosystem that supports the cooperation.
- Data quality To ensure that the information is precisely, completely and reliable (because poor data is worse than no data).
- Ruling To establish possession and accessibility so that the teams stop working with their own contradictory versions of truth.
- Implementable knowledge Focus on what the data mean instead of reporting what it says.
A properly executed UDS changes the functioning of marketing teams. With a UDS, teams have the option:
- Make clever decisions. No more guesses or intestinal feelings – you will have reliable intelligence, all teams agree to.
- Do you provide really personalized experiences. With a UDS you can no longer rely on generic segments and start adapting interactions based on the actual customer behavior.
- Increase efficiency. They spend less time to repair bad data, to reconcile reports and to discuss contradictory KPIs.
- Ensure conformity. A structured, governing approach helps you to develop with GDPR, CCPA and further develop and develop data protection regulations.
The next step: data alone will not save you
It is easy to believe that a new software platform or a more sophisticated algorithm will magically solve your data problems. If the purchase of better software were everything it needs, every marketing manager would be a genius.
Effective UDS is not about more software, dashboards or numbers. It's about something more fundamental: team and process.
Too many marketing teams focus on what (technology for collecting and storing data), but neglect that how and the WHO.
The challenge is to tackle the organization of data and not just the tools. By solving the change of perspective, it changes from a technologically centered view to a human-centered.
An effective UDS requires all three elements:
- The right technology: Yes, technology is essential. But it's not just about having the latest and biggest. It is about selecting tools that enable cooperation and optimize workflows. It is about ensuring that the data is uniformly, precisely, implementable and accessible to the entire team. Remember to build up a common language, not just a data warehouse.
- The right attitude: Here the team really comes into play. Data sharpness mentality creates silos and hinders progress. However, the promotion of a culture of data exchange and cooperation does not require extinguishing. You can leave these silos standing if you focus on creating a collaborative communication between you and enable everyone to contribute to your findings. The aim is to create a common understanding of the value of the data and how teams you can use to achieve common goals.
- The correct execution: Even the best findings are worthless if you do not implement yourself in action. You have to define a process to convert data into implementable strategies. This means that workflows are defined so that teams can react quickly to changing market conditions and customer needs. It also requires that insights into the daily work of each team member are integrated.
How to create this human-centered uniform data strategy
The solution lies in the creation of a cross-functional data team, which brings compotation from different departments together, sales, product and customer service.
This team will be responsible for:
- Define clear data government guidelines By determining guidelines for data acquisition, storage and use.
- Development of standardized data definitions and metrics To ensure that everyone speaks the same language.
- Creating a data -controlled decision -making process This describes the process of how data influence strategic decisions.
- Provision of ongoing training and support To enable team members to use data effectively in their work.
I examined all of these topics in a research work (registration required) that I created for Velir. If you are interested, download it to determine whether this approach swings with you.
One thing that I know with certainty: So that a uniform data strategy is more than 2025 of the 360-degree customer view, you do not need any further data. But they will need more daring.
Dare to create processes that work across silos. Dare to strengthen your team. Dare to look beyond the numbers of human history that you tell.
It's your story. Say it well.
Subscribe to On the working day or weekly CMI emails to get pink glasses into their inbox every week.
Hand injured content:
Create your very own Auto Publish News/Blog Site and Earn Passive Income in Just 4 Easy Steps
