Why Marketers Can’t Ignore Data Quality
We talk to a lot of marketing leaders. Consistently, they want to understand their customers, optimize their campaigns, and above all, bring personalization at scale to life. They are often looking for great orchestration tools, better ways to segment audiences, and more automation and triggers. But most aren’t asking about data quality.
That’s a problem. Data is a marketer’s golden ticket to knowing customers and driving revenue. It tells you who your best customers are, how to engage them, and how to acquire more great customers. But if the data you’re using is sparse, duplicative, erroneous, or incomplete, your campaigns will miss the mark.
Don’t take our word for it. Forrester and media measurement platform Marketing Evolution published a study this summer that showed some eye-opening statistics: 21 cents of every media dollar spent is wasted and 26% of marketing campaigns are hurt due to poor data quality.
How is this possible? It’s simple. When it comes to segmentation, targeting, and personalization – it’s garbage data in, garbage results out.
For example, most brands try to acquire new customers that look like their best customers. They send lists of their highest value and most engaged customers to social media or other ad platforms for lookalike modeling. They also use CLV to triage call center and support, reducing costs while increasing loyalty. These are just two examples, but there are many applications for “best customer” segments.
But in order to know who your “best customers” are, you need clean data from point-of-sale, eCommerce, and 3rd party sellers. You need a historical view of their engagement and a recent one. You need to account for returns, ratings, and reviews. All of this data must be accurately unified in a way that’s relevant to your particular business.
Building this segment requires advanced identity resolution capabilities because most brands’ best customers engage across many channels, use multiple email addresses, and change addresses and even names throughout their relationship with a brand. Maintaining this segment means an always-on system that moves customers in and out as they purchase and engage. “Knowing” your best customers is harder than it sounds.
Amperity was built to give brands the highest quality view of their customers possible. Before Amperity, brands are, on average, misidentifying 17-24% of their customers, representing 40-47% of overall Customer Lifetime Value. This is just one example of poor data quality. Other segments including “likely to churn”, “likely to purchase” and others key insights are also typically just as erroneous.
The Amperity platform employs a proprietary approach called Fusion, which uses artificial intelligence to accurately link records that legacy approaches like hand-coded business rules routinely miss. Our customers see a 993% ROI using Amperity, simply by powering their segments and campaigns with a truly accurate, 360 degree view of their customers.
Don’t base your marketing ROI on poor quality data. To learn more, visit https://amperity.com.