As CMOs and chief storytellers, it’s our job to convey the impact of marketing as part of the story. We can explain – better than anyone – customer experience and engagement opportunities by interpreting data from buyer touchpoints. From prospect data to closed deal rates to marketing campaign performance, we can weave data into a meaningful narrative that justifies our strategies and (hopefully) wins more budget share for new programs.
The catch is making those stories meaningful. With high-quality data, you can tell an insightful story and confidently explain the influence on revenue and brand loyalty. Your C-suite peers may question you, but if you can explain how you came to your conclusions based on data, you’ve got your impact story.
Simply taking the numbers from your trusted team without asking how the data was compiled and sourced is a big mistake. Use inaccurate data and the story becomes misleading, causing you to make faulty marketing decisions and invest in the wrong campaigns. Even the best data maintenance leaves room for errors, given the sheer volume of information we deal with every day. That’s okay – what matters is distinguishing between what’s accurate and what’s faulty, subjective or unhelpful.
Here’s what good data quality looks like:
- The data is as complete as it needs to be. Customer names should have phone numbers and email addresses attached to them. Company names need to be complete and correct titles should be included. Existing buyers are associated with their buying history.
- Each data record is relevant and unique. Duplicate data wastes time and money. You need to establish thoughtful business rules for sourcing and combining data from multiple sources in order to create a single record for each unique entity.
- Your data is accurate and current. If old data is mixing with more recent updates, and you’re not sure which is which, you’ve set up your team to work from a distorted picture. Good data includes details from the last engagement date.
- Consistent patterns and terminology keep your data manageable. With multiple systems feeding your data, it’s easy to collect phone numbers, last touch date, birthdates, titles and more in a variety of formats. This can lead to duplicate data sets or correct information discarded in favor of incorrect data.
With big data showing no signs of slowing down, developing a smart data cleansing program is mandatory. So how do you keep your data in top condition?
Pay attention to the big picture.
As CMO, you may be the only leader to see how the numbers from every customer engagement touchpoint, campaign and angle fit into one cohesive customer experience story. Research and develop benchmarks for the industry and for each methodology and source so you can put metrics in context to detect trends.
Also important: interpreting data for each pipeline stage so you can diagnose any problems in sales and marketing alignment. For instance, if you have low sales accepted leads, you may need to reexamine your lead qualification criteria for better quality. If you have good sales accepted leads but low sales qualified leads and high lost rates, you may have a noncompetitive solution or a sales team with poor selling skills.
Dive into your sales and marketing tech ecosystem.
By understanding how data flows across your marketing automation and CRM systems, as well as any reporting tools and compliance processes, you’ll spot possible channel conflicts and sources of incomplete or conflicting data. For instance, maybe your vertical classifications seem all over the map and are not aligned across systems. Perhaps your data capture cookies are scattering data instead of directing information to the right records.
By understanding your data and systems infrastructure, you can tighten up your database and the reporting results for better insights.
Develop an efficient integration system.
You can almost guarantee that different databases will have slightly different sets of the same information, creating an abundance of errors and duplicates. Is this easy to resolve manually? Not if you have a sizable data trove fed by a significant number of systems. Instead, use good data quality tools to identify your data and organize it in a consistent, modern way.
You’ll need a master data management (MDM) tool to build a single master record (sometimes called a “golden record”) that gives a composite view of your data. You can then build a data subset for your marketing needs and have the right rules for synchronizing your data across teams and systems. If your CRM system has different core contact information than your marketing automation system, sales and marketing alignment will be at risk.
Tap third-party sources.
Trying to build an effective approach on partial data can be as futile as having no data at all. Since you’re unlikely to collect a complete and comprehensive data set on every single prospect, consider supplementing what you do have by acquiring high-quality data from third-party sources. Predictive and intent analytics can provide a wealth of helpful data to prioritize both accounts and contacts for the right outreach.
Set your data system up for success.
Your data will grow as your customer base grows. Your future will contain new markets, new customers, new prospects and new tools – so make sure your systems are clear, organized and ready to scale now. Staying on top of your data quality can create a ripple effect of greater conversions, stronger customer service and higher-performing campaigns. But it will also lead to reporting that drives your marketing and sales strategic insights. That’s a story you’ll want to tell your other leaders again and again.
