Why cleaning your brand’s data is to key to improving accuracy and relevance
The goal of marketers is to provide customers with an outstanding experience that delights at every touchpoint and exceptional enough to ensure each individual’s journey ends with a purchase. But sometimes, we find that even when marketers think they are putting their best foot forward, some customers never respond.
Are brand marketers missing the mark? Or is their brand’s poor data-keeping practices preventing them from even reaching their customers in the first place?
There are a number of reasons behind why many communications remain unseen and unacknowledged. Maybe a customer’s information has changed, or maybe brands are sending messages via channels unused by the proposed recipient. Perhaps a brand’s protocol is so unstructured that is appears as spam and goes straight into junk mail.
A recent report from McKinsey highlighted the extent of this wasted opportunity by claiming businesses “leak” about 90% of the potential value their data ought to deliver. This leakage is leading marketers to miss out on a huge range of marketing opportunities and all because their brand lacks up to date, “clean” data.
To stay top of mind, all brand marketers must find a way to keep customers engaged on their preferred channels. For many organisations, the most effective route to achieving this is routinely cleaning their customer data. Doing so ensures the data they are using to reach and market to customers is as relevant and accurate as possible.
Why does my data need a clean?
Marketers know how important customer data is to their daily job and results. However, many are not fully aware of the dangers “unclean data” can have on marketing efforts.
First and foremost, inaccurate, “bad” data affects customer engagement and brand reputation. Outside of just email addresses, many brands keep names, birthdates, addresses, and more. When a contact sees an email with the wrong name or with her name misspelt or receives an email for a birthday in the wrong month, this can leave a negative impression of the brand. Rather than getting a personalised experience, people are receiving messages that does not make them feel understood at all thereby eroding confidence in that brand.
Data cleaning is a key tool then in defending against this outcome, and can be supported by business-customer data transparency initiatives. Every customer should be kept in the loop on how a business plans to use their data for their benefit – this can be in the form of a simple interaction that asks whether they would still like to be contacted. Businesses must remember that they do not own data, they borrow it, so giving an opt-in/out option can help businesses ethically clean-out redundant data while at the same time increasing trust.
Avoiding damage from “unclean” data
Secondly, brands with out of date data are damaging their ‘sender scores’ more than they realise. Those that batch and blast messages to every email in their database are doing themselves more harm than good, because if any of these addresses are no longer used, no longer valid, or belong to someone who doesn’t want a certain brand’s emails, it’s a practice that will damage that brand’s sender score. Crucially, this metric can actually keep businesses out of their customer’s inbox - the lower the score, the more likely they are to end up filtered out and into a spam folder.
A spring clean to boost productivity
Furthermore, ‘clean’ data also makes businesses more productive. When brands have data that is clean and usable, they can use machine learning tools to quickly create campaigns that efficiently execute on that data. When data is incorrect, these businesses spend more time manually editing campaigns.
Marketers who work with accurate and complete data also have more freedom to focus on the strategy and creative behind their campaigns, allowing them to be more engaging and in turn, drive higher conversions.
When thinking about clean data, it can be hard to decipher exactly what qualifies as ’clean’. To keep it simple, think of clean data in these two ways – accurate and complete. In terms of accuracy, data is considered accurate if it is the most up-to-date as possible. Yet for data to be complete, businesses must increase their knowledge of customers’ preferences whenever possible to build a more comprehensive picture of their needs and frequent interests.
Cleaning is easier than you think
Getting your data in order doesn’t have to be outsourced, and it doesn’t have to consume all of a marketing team’s time. The best way to target the correct audience is by asking your customers if they really want to be marketed to. For marketers, an email address is like liquid gold, so it may seem counterintuitive to ask contacts if they want emails from you.
However, customers that opt-in to communications with brands are the most engaged customers, and far more likely to convert than contacts who have no interest in receiving marketing communications. As marketers, our job isn’t to spray and pray our way to sales - it’s to provide the best possible experience to our target audience and delight them to the point of purchase.
In the post-GDPR era more brands should also consider regularly sending a “break up” email to customers who haven’t engaged in a few months. Contacts who open and opt-in can remain in the database and stay engaged with the company, and those who don’t can be easily cleaned out.
Another option for cleaning up your data is sending a “We miss you” email. These emails not only re-engage defecting customers with attractive discounts, but also encourage contacts to further complete their profile. For those that do re-engage and purchase, it’s also advisable to request additional information from them to complete their order. For brands, this helps them obtain more accurate data through the customer’s own voluntary action – ultimately improving their user experience.
By and large, email addresses and payment information are often the only requirement for checking out on e-commerce sites. Yet sometimes, that data changes and the customer isn’t quick to update their information. One option for brands to clean out old data is to also include an “Edit Your Profile/Preferences” call to action in emails. This gives customers the option to update their preferences (how many and which emails they receive, if they want to receive SMS offers) and update their contact information proactively as it changes.
How to avoid the bad data problem
In our digital world, data is everywhere. This makes the challenge of keeping accurate, actionable data even more complex for brands and businesses. With a straightforward data cleaning strategy however, brands can boost the value of their data in ways that are far more straightforward than they appear. Above all, when cleaning data brands must always remind themselves of the main reason for doing so – providing optimised, personalised services to their customers.
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