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Unifying Marketing Data Governance Practice: How to Build your Business Case

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Written By Adeyemi Adetilewa

Building your case for unifying data governance practice and consolidating taxonomies is extremely challenging. However, unifying your marketing data governance practice is vital for marketers in order to deliver personalization.

It is also vital if you are to scale up your marketing campaigns and accurately measure your returns on investment (ROI). In this post, we will look in greater detail at why this is important and how you can build a business case to support this.

The Challenges of Data Consistency

Achieving data consistency across an array of marketing campaign areas can be hugely challenging. However, the costs of inconsistent data, and the confusion this causes, should be carefully prevented.

For example, a successful campaign could be made up of 4 key areas. Each of these areas will have its own unique metadata. But if they also have their own unique metadata definitions, things can fast become confusing.

When definitions and metadata elements are inconsistent across marketing campaign areas, such as campaigns, catalogs, content, and coupons, marketing insights can be negatively affected.

On the one hand, they could be only partially true, and on the other, they could be based on false information or conclusions. Neither of these is ideal and both make it nigh on impossible for marketers to deliver the sorts of measurable results they need to maintain or grow their budgets.

4 of the major signs of issues with data consistency and poor data governance include:

1. Confused taxonomies

When names and definitions are so confusing and conflicting, marketing teams can be forced to constantly create new ones.

However, whilst this might be essential for their marketing campaign to progress, the constant generation of new taxonomies feeds into an already confusing taxonomy! This creates a negative spiral of increasing complexity.

2. Poor centralization

As tempting as it can be for individuals to have their own spreadsheets, this can soon see taxonomies spiral out of control. It is much better to get buy-in to centralized systems of control to prevent taxonomies from becoming confused.

3. No framework

If no single document exists defining every taxonomy and their associated metadata tags, marketing teams won’t be working on complete information. Indeed, they may simply be working on the shared knowledge ingrained within team cultures, rather than truly exploring the underlying data.

4. Low growth in customers

If the input of marketers is not leading to increases in sales or new customers, this can be a sign of poor or incomplete marketing analytics. It is also important to launch campaigns with a clear understanding of the complete experience data model and consistent metadata.

Understanding the importance of experience data models

Unifying Marketing Data Governance Practice Easy Guide 2021Incomplete experience data models are costly. This is because they are likely to be riddled with inconsistencies in data and poor overall data quality.

This happens when people are forced to make new taxonomies for multichannel campaigns, without any proper oversight.

As a result, marketers will be unable to drive sales effectively, potentially preventing growth in company revenue. As such, incomplete data models can be one of the most costly issues for marketing organizations. 

The 4 key ways inconsistent experience data models reduce the effectiveness of marketing:

1. Time costs

Launching multichannel campaigns when working with poorly integrated systems, multiple metadata definitions, and confusing taxonomies costs you time and money. Decisions and strategies will also be hampered.

2. Duplicated MarTech stacks

When working across regions and with different markets, it is common for people to create duplicate or even different MarTech stacks.

Unfortunately, this makes it difficult to create a single experience data model resulting from inconsistent metatags. If the ultimate goal is to deliver a unified strategy for multichannel marketing, multiple MarTech stacks will slow things down.

Integrated MarTech stacks and complete experience data models ensure improved accuracy, speed, and scale.

3. Inconsistent experience data models

From random metatag definitions to the absence of consistency in naming campaigns, poor quality experience data models limit marketing’s ability to succeed.

These issues are exacerbated by a lack of data governance. Indeed, a lack of data governance makes it impossible to know the true effects of a marketing campaign.

4. Increasing data dependency

Poor quality data governance + inconsistent experience data models = poor quality data. Given the growing importance of data to successful marketing campaigns, and knowing why things work or not, this is a recipe for disaster.

Given marketing budgets rely on measurable results from the last quarter, this can lead to a downward spiral fast. It is vital to be able to track the right user against their experiences, on the right device, and the data collected is a true representation of events.

This is only possible by unifying marketing data governance practices and operating with a unified taxonomy.

What is change management?

If you want to deliver high-quality customer experiences, then you need to be able to effectively track how they progress towards their personalized expected goals. If you recognize any of the issues explored above, this will be a challenge you are likely to face.

However, fortunately, you can soon turn a disjointed or non-existent experience data model into a fully-fledged and unified marketing data governance practice. The key to achieving this is getting change management right.

Change management means getting buy-in across your organization. It needs everyone to believe in the changes being made and finding unity around a single enterprise-wide taxonomy.

This will ensure people’s jobs get easier whilst giving them better quality access to higher quality data. It is vital to have leaders who understand the importance of change management who can also communicate this importance. 

A key component of change management is also empowering teams to feel in control of decisions, whilst providing a sound overarching structure.

Combining automation with increased control over workflows helps to offer improved data governance alongside increasingly dispersed ownership and control over workflows. Teams with ownership are also much more motivated, offering support for integrating automation into change management approaches. 

What are the benefits of adopting a unified marketing data governance practice?

Unifying Marketing Data Governance Practice Easy Guide 2021Once team buy-in to change management has been achieved, adopting a unified marketing data governance practice can be put into place. Here, we outline 6 of the top benefits of achieving this:

1. Improved personalization at scale

Multichannel marketing campaigns can rely on huge numbers of unique data points. These are used to track how a campaign has been executed and to try and monitor the proper functioning of all aspects of the campaign.

With a complete experience data model, it is possible to cover both content creation and marketing campaigns. This is essential when delivering personalization, particularly when scaling things up.

Delivering improved personalization obviously helps to improve customer experiences. However, doing this in a structured way ensures these experiences are shared organization-wide and across all channels.

2. Enforced & a unified taxonomy

With buy-in from marketing teams, enforcement of a single, unified taxonomy will be simple. It is important then that everyone understands why a unified taxonomy across all areas is important.

This means from products to service groups and marketing to sales, everyone needs to comply and believe in the unified system. This will bring benefits for time savings, improve cross-departmental collaboration and understanding, and ensure improved investments.

This level of unified marketing data governance practice is necessary and vital for large-scale businesses and marketing firms.

3. Reduced complexity

A unified taxonomy has benefits in terms of reduced complexity. It also ensures marketers can feel confident in the data they use. This means they can spend more time building macros, designing URL structures, and tackling mobile app dependencies.

They can also spend less time worrying about how clean and appropriate the data they are working with actually is. Ultimately, a single taxonomy and clear data governance structures combined can save thousands of hours to marketing teams.

This massively boosts productivity and offers the potential for huge savings in salary costs.

4. Unified campaign and experience tracking

When campaign and user experience tracking is unified across all channels and platforms, numerous roadblocks are removed. When metadata is consistent across channels it becomes easier to measure results accurately, design new campaigns, and launch them.

It is also possible to accurately monitor progress over time with common metadata ensuring shared definitions equate to comparable data. This greater understanding of changes over time will ensure savings are made when they can be and decision-making is improved.

5. Budgetary gains

As already alluded to above, budgetary gains are a major selling point for unifying marketing data governance practice. Indeed, each of the advantages listed offers various budgetary gains.

However, in any business case mentioning budgetary gains in its own right is important. When it comes to supporting unifying marketing data governance practice, it is clear to see how a single taxonomy, compared to 20, 30, or more, can lead to huge cost savings.

Indeed, many firms find they can rely on fewer additional licensing costs by working in this way. Conservative estimates put the savings from this approach to be over $200,000 on IT budgets alone. That is before the benefits of working with better, less complex, and better-organized data kick in.

6. Improved insights

Data is increasingly important. However, be sure the data you are working with is even more important.  Good data governance and unified marketing practice with a single taxonomy help to ensure this.

With all marketing teams working in alignment with a shared taxonomy, following naming conventions, and to agreed standards, you know the accuracy of your analytics will improve. Improved analytics leads to improved insights.

Improved insights ensure the decisions you make are the optimal ones available, helping you to be more agile in volatile markets.

What are the costs of adopting a unified marketing data governance practice?

It is clear that there are huge benefits in terms of cost savings by unifying your marketing data governance practice. However, there are also associated costs on the road to these savings. These costs will include any upfront costs payable to your chosen data governance platform.

You will also need to pay for the annual maintenance of this new platform. In terms of facilitating integration, you will also have new expenses regarding change management (generating buy-in), actual implementation (roll-out), and regular audits (monitoring and maintenance). 

Other costs will include:

  • Initial training costs (e.g. how to use your chosen data governance platform)
  • Ongoing training costs
  • Launch costs 
  • Auditing costs

Whilst these costs can be off-putting to some, you will soon see these costs offset by the savings afforded by improved data and reduced complexity.

Indeed, increasingly complex systems can quickly lead to spiraling costs that hamper growth as well as reducing overall data quality and control. Fortunately, you won’t have to wait for an age for your initial investment to bear fruit.

How to create your business case

Unifying Marketing Data Governance Practice Easy Guide 2021It is important to quantify the benefits of a unified marketing and data governance approach when making your business case. The costs associated with the process of change can be forecast against potential savings, benefits, and data quality.

A simple calculation of ROI can be calculated based on the expected benefits of change minus expected costs, then divided by the expected costs, before being multiplied by 100.

This calculation can be monitored quarterly and annually, to ensure ongoing buy-in for the overall process of continuous improvement good data governance demands. For medium-sized high-tech firms, an ROI of $4.75 for every $1 of investment is often actually a conservative estimate.

Summing up

Building your business case in support of unifying marketing data governance practice is simple. The cost benefits are a no brainer, but they stem from the quality of data and ease of use of the overall system that is created.

By standardizing multiple complex taxonomies into a unified system across all areas, automation of governance is easier, and marketing can rely on the quality of data being used. 

Results can be captured in real-time, ensuring agility and cross-enterprise integrations become simpler. This can lead to fewer external contracts and increased internal collaboration. Ultimately, with incredible ROI, a unified marketing data governance practice largely makes its case for support all by itself. 

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