Marketing Data Analytics: Can You Trust Your Source of Truth?

Post by 
Kenneth Shen
Published 
May 7, 2021
S

o you’ve already set up your analytics infrastructure to track all your marketing activity and report the data? Great!

But… how well are your data-capture processes accurately reporting the metrics that are important for your business? And is your data really telling you the truth, the whole truth and nothing but the truth?

If not, trust me when I say it’s costing you. Business performance actually hinges on data integrity more than many SME businesses realize. Simply put, data drives revenue. It’s the engine of your business.

The goal of this article is to get you working with a complete and correct data set on an ongoing basis. After all, the insights you can gain from data will only be as good as the data itself.

To clarify the terminology, data integrity is the completeness, accuracy, and consistency of data over its lifecycle. Data hygiene refers to the process of ‘cleaning up’ data.

Let’s have a look at some best practices to ensure your marketing data has optimal integrity, to ultimately help turbocharge your business growth.

We’ll then discuss how to use data visualization to fully harness the available insights of your marketing data in our next article.

Skip to What You Need:

Consequences of Poor Data Integrity

Poor data is rarely blamed for stalling business growth. However, ‘dirty’ data results in reduced clarity, poorer decision making, less marketing efficiency and ROI. This invariably impacts bottom line financial results.

Poor data integrity typically means that you will be unable to:

  • Segment your target audience
  • Track the source of leads and conversions
  • Track spending accurately and break down where budget is spent
  • Assess ROI of marketing activity and campaigns
  • Improve ROI through accurate performance assessment, divesting from ineffective tactics and optimizing the most effective tactics

Without fully comprehending the impact of bad data, many SME businesses are often sorely lacking necessary data protocols and checks. 

The end result is that sales leads and customers are lost, marketing insights are inaccurate or unavailable, and remedial decision making is poorer.

Creating A Data Integrity Culture

Optimizing your data integrity requires a hygienic data culture through controlled processes. And just as nothing is static in your market place, with your customers, in marketing practices, technology and platforms, your data quality control processes can’t be static either.

Get Focused With Your KPIs

Start by determining what Key Performance Indicators (KPIs) you need to report. This naturally determines what data needs to be tracked to provide the necessary metrics. 

Your KPIs should be based on overall business goals, and specific to your supporting marketing strategy, tactics and campaigns. There’s lots of content out there about which marketing KPIs to use.

Use your KPIs to provide clarity around your audience characteristics and behavior, the effectiveness of individual marketing campaigns and direct revenue results. Keep them tightly focussed, and make supporting metrics easy to report. That way, you can see exactly how your marketing activity is performing at any given point in time.

Make sure you’re also informed about what kind of metrics and reporting are available to you within your marketing tech stack. There might be some helpful metrics that you’re not utilizing yet. 

The completion of an annual marketing audit and plan is an ideal opportunity to review overall objectives and supporting KPIs in use. However, this should also a live, ongoing process as campaigns progress and necessity dictates.

Formalize Data Hygiene and Governance Processes 

Whichever tactics you decide to implement for managing your data integrity, there are 4 overarching pillars to build your hygiene process upon. 

Audit, Correct, Validate and Automate.

1. Audit

Review the data you’ve already got. Determine how far it is:

  • Complete - Do your current data-capture processes provide metrics for all of your marketing KPIs? Where are the gaps?
  • Accurate - Are there errors within the data? Or duplicate entries?
  • Consistent - Is the same data captured every time? And can all data be quickly and easily pulled into a report without time spent cleaning and preparing it? E.g. by having to manually standardize values, or merge data spread over more than one field.

Your audit should also identify any unnecessary data capture. Make the data-capture process user-friendly for your customers and staff. Only collect and store data that’s actually necessary and helpful for decision making.

Legal compliance needs to be considered too. Confirm that your data does not overstep relevant laws to safeguard people against unwelcome communication and protect their personal data.

Ensure you audit all platforms leveraged to collect information from customers, not forgetting sources such as surveys, webinar registration forms, and demo or download forms. Look at how that data is integrated within your main CRM system.

2. Correct

Based on the results of your audit, where do tighter data hygiene and governance processes need to be introduced? And are there steps you can take to clean up the data you already have?

Manual data cleansing is laborious and often uneconomical. If it’s too time consuming or not possible to correct past data, just focus on how capturing the accurate and consistent data that you need going forward. 

There are also data cleaning tools out there that can help you if budget allows. Cleansing systems are able to scan masses of data and use algorithms to detect duplicate records or anomalies resulting from human error.

3. Verify

Follow on from the first two steps by testing and verifying that the data that you are now collecting is consistently and accurately being recorded. 

Can you quickly and easily pull together KPI metrics using your improved processes?

4. Automate

Once you’ve verified the suitability of your updated process design and data governance rules, integrate them into your marketing operation as the new norm. 

Do this by designing a systemized and documented workflow, communicate it across all relevant teams, and regularly check that the rules are being adhered to. Use automation and data validation where possible to avoid human error. 

Use this 4-step hygiene process as you undertake campaigns, as well as within your annual planning. And don’t forget to check what new validation or automation technology might be available since the last review. Options, technology and price points regularly evolve.

Summary

The value of good data compounds over time. Better data means better insights and decision making. Combined with know-how to interpret good data, the result is more effective marketing and customer communication. It will drive your brand impact and business growth for less financial investment.

Creating a holistic data capture process that maintains data integrity at each stage takes some knowledge, investment and continued prioritization. A well-designed data system should function like a supercar, with each component fully optimized and working in harmonious synchronization.

We’ve covered a lot here, and I know it can be overwhelming. If you need any support, please just get in touch with us at Half Past Nine to discuss what support you need. Data is our truly our passion, and we’d be delighted to help!

What to read next:

Marketing Data Analytics: Building Your Source of Truth

Marketing Data Visualization: Communicating Your Source of Truth [Coming Soon]

Actionable Strategy
Direct-To-Inbox.

We never share your info. View our Privacy Policy
Welcome to the Club 👋
Sorry, something went wrong. Can you try again?