How do I fix inaccurate marketing data?

Read time: 7 minutes

By now, there's no denying that data is one of the most powerful tools in your marketing tool belt.

Collecting key information allows you to understand and connect with customers on a much deeper level. It enables you to personalise communications, tailor your content output, understand who your target audience is and so much more.

But over a quarter (25-30%) of data is deemed to be inaccurate within a year and this inaccurate data could be costing businesses up to 20% of their revenue.

And these figures are even more concerning for B2B data, which decays at a rate of around 70% per year.

Database accuracy is never guaranteed at 100%. Every day, data changes due to people changing and altering their roles. Given this nature of B2B data, it is crucial to understand the expected quality level and the procedure for flagging inaccuracies.

- Maco Dimayuga, Head of Global Data Operations

It's a big issue for businesses as inaccurate data doesn't just impact the bottom line, it's also a significant drain on marketing budgets and can lead to costly, ineffective campaigns.

Being saddled with underperforming and inaccurate data can feel like being aboard a sinking ship, but don’t give up just yet: there are a few key things you can do to turn it around.

Here are six ways to fix inaccurate marketing data and instantly increase the success of your campaigns.

What causes inaccurate data and how can this impact your campaigns?

According to Statista, the biggest reasons for inaccurate data are:

• Customer errors (35%)
• Fake data/bots (29%)
• Employee errors (27%)
• Old/degraded data (26%)
• Data not being cleansed (26%)
• The source of the data (22%)

All of these reasons can lead to customers receiving irrelevant marketing communications and annoying targeted ads. Which in turn, can lead to them unsubscribing from your services, taking their business elsewhere or even boycotting your brand.

Recommended reading: Personalisation is only as good as your data: Improving data accuracy

What happens if bad marketing data isn't fixed?

When left unchecked, inaccurate data can have severe and widespread repercussions in a business. Not only is it likely to have a high impact on productivity, it paves the way for a rise in inefficiencies as teams struggle to make sense of the data they have.

Trust is built upon accurate information, thereby boosting brand reputation, and nurturing genuine customer relationships.

- Maco Dimayuga, Head of Global Data Operations

Businesses are also likely to experience reputational damage as customer and employee mistrust grows due to poorly delivered messaging. This adds fuel to the fire in terms of lost revenue and opportunities for growth.

Then there's the added issue of compliance fines and the risk of damaging partner or supplier relationships, which further impacts your operations and is likely to cost you loyal customers. 

The simple issue of inaccurate data can't be kept in silo either and will quickly spiral into other teams, creating company-wide problems that can be difficult to fix.

 Difficult, but not impossible. So how do you fix data inaccuracies before they become too much of an issue?

6 fixes for inaccurate marketing data

Yes, a database filled with duplicate records, incorrect email addresses and quality issues is a problem. A big problem. But all problems have a solution. Here are six things you can do to address and correct your poor data quality:

1. Check your data sources

The first thing you need to do is to consider where you're getting your data from and if your sources are reliable and high quality. Then, make sure you're using the right platforms and tools to collect and store it.

You need to determine whether these sources are up to date, configured correctly and well maintained. If you notice that any of your sources are causing data errors, it might be time to rethink your strategy, as well as where and how you're gathering your data.

2. Regularly cleanse and update your data

Another simple but effective way to remove or fix any inaccurate data is to audit and cleanse your database to remove duplicate, outdated or irrelevant information on a regular basis.

Start by conducting a thorough audit of your marketing data to identify any visible inaccuracies. You should look for discrepancies, missing information and any inconsistencies across different data sources.

Once you've done this, you can then start to regularly cleanse your databases. Consider implementing data quality tools and software that can help to identify and correct inaccuracies automatically. These tools should include features such as deduplication, validation and cleansing.

You can also ensure the accuracy of your databases by regularly updating and verifying customer information.

3. Implement data validation processes

If you set up the correct data validation processes, you increase your chances of catching errors in real-time, before they have any sort of negative impact on your marketing campaigns.

The highest quality data typically originates from human verification processes. Merely having a large volume of contacts doesn't guarantee usefulness, as incomplete data points, such as missing email addresses, can be just as detrimental as inaccurate information. Marketers should exercise caution regarding contacts with empty data fields and data derived from automated guesses.

- Maco Dimayuga, Head of Global Data Operations

There are different validation rules and checks you can introduce to ensure data accuracy at the point of entry, whether that comes from customers or employees. For example, data type checks - as the name suggests - will confirm whether or not the information has been entered as the correct data type.

Similarly, format checks make sure that any information entered into your database or CRM matches the correct format and consistency checks can be used to ensure data is entered in a logically consistent way.

By getting the correct validation process in place early on, you can stop inaccurate data from ever making its way into your databases.

4. Standardise data entry across the team

It’s also important to establish and enforce standardised data entry practices across your teams and departments to help reduce errors.

Automate data entry processes as much as possible, but make sure you have the right validation processes in place at the same time. This reduces the risk of human error.

The tech, however, is only half of it. Make sure that all members of the team receive training on consistent formatting and data input guidelines. This should be ongoing training, especially for your marketing and sales departments.

Everyone needs to learn about the importance of accurate data - not just the marketing team - so you can foster a culture of data quality within your organisation.

5. Encourage customer feedback

One of the easiest ways to verify customer data is by encouraging them to provide feedback on their information.

For example, when speaking with existing or prospective customers sales reps can ask them to confirm their email or phone number before moving on to the next stage of the conversation.

There will, of course, be contacts in your database that aren't ready for a sales call yet. They might not even be actual customers yet there, but a marketing lead that's subscribed to your email newsletters or regularly receives company updates. Use your email campaigns to encourage them to double-check and verify their own information.

You could also use this strategy to ask for general feedback on the company, allowing customers and prospects to share their experience with your brand and give their opinions on the marketing communications they receive. As they submit this information, ask them to re-enter their details. This not only allows you to correct inaccuracies and update records but also gather genuinely helpful insights that can be used elsewhere.

6. Continue to monitor and measure your data quality

It’s crucial that you continue to monitor and measure your data quality and put effective processes in place to ensure your databases are accurate (and remain so).

The best way to do this is to set up key performance indicators (KPIs) or goals to track the accuracy and completeness of your marketing data. This will give you direction and tangible results that allow you to keep an eye on your performance and the accuracy of your data going forward.

Everything is fixable, even inaccurate marketing data

Customer data management requires constant attention. And as soon as poor-quality data starts to creep in, things can go quickly from bad to worse. Which also means your marketing efforts are likely to get derailed and campaigns put on hold.

It's a difficult and frustrating problem to deal with.

The good news is it's fixable. It could mean your marketing campaigns are paused a little longer than anticipated while you work out how to fix the accuracy of your data, but that doesn't mean your pipeline has to go cold. 

At Intentify Demand, we employ both human-verification and machine-verification data processes. Human-verified data undergoes confirmation by our world-class data research team, which means its reliability is significantly higher. Meanwhile, machine learning algorithms are employed to gather and verify machine-processed data, resulting in vast datasets. However, without human oversight, these algorithms may generate inaccuracies or include outdated information.

- Maco Dimayuga, Head of Global Data Operations

If you'd like a helping hand with keeping your marketing funnel warm while you fix your data issues, then feel free to get in touch. Or if you want to level up your data platform, take a look at our handy guide below 👇