I generally think of myself as one of the cool kids when it comes to marketing. I try to stay on top of the trends to remain relevant. These days the focus is more on digital, social and all things flashy and new. A quick google search on Marketing Trends 2015 yields results almost entirely focused on digital marketing even though I purposefully left “digital” out of my search.
That was surprising.
Don’t get me wrong. I’m excited about the possibilities opened up by this new fan-dangled digital technology. However the mom in me wants to slow the roll a bit and make sure we don’t get too far ahead of ourselves.
Having a solid foundation on which to build all marketing efforts has never been more critical. I may start to get a few eye rolls when I mention the importance of data quality and consumer recognition as a key building block ESPECIALLY as it relates to digital. These topics may not be as popular or fun but I assure you they are crucial to your marketing success.
Cleanliness is next to godliness.
Why should digital marketers care about clean data? Some may argue that digital is more agile and cost effective which outweighs the need for stringent data quality. That may have seemed to be the case early on but as we start to bring together and analyze the data, we have found that bad data can prove just as costly through misinformed decisions.
Think about the decisions made based on inflated views on Google/YouTube by bots a few years back. Buying decisions were made based on the inflated results. Similarly, data redundancies yield inflated metrics which leads to higher costs and wasted marketing spend.
This room isn’t going to clean itself.
And neither is the data.
Back in my day when computers were just coming into the mainstream, the term GIGO (garbage in garbage out) was heavily used to remind us that the integrity of the output from a computer program was directly correlated to the input. This concept is just as relevant to marketers today.
A “Data Quality and the Bottom Line” study completed by The Data Warehousing Institute (TDWI) stated, “The problem with data is that its quality quickly degenerates over time. Experts say 2% of records in a customer file become obsolete in one month because customers die, divorce, marry and move.” Think about the impact of throwing that much garbage into one of your most important assets each and every month.
Data quality validates, corrects, completes and enhances the data captured from consumers across touch points and throughout the life cycle. As data is passed downstream into other marketing systems, the inaccuracies are amplified. Everything from inflated tagging, to call center keying errors and ever-changing personal identities impacts the effectiveness of downstream marketing activities.
You are getting on my last nerve.
Gaps in data quality and consumer recognition can also damage brand reputation and negatively impact the all-important customer experience.
Nothing turns me off of a brand more quickly than irrelevant and/or inconsistent messages.
One of my biggest pet peeves is receiving a better offer on a banner ad (as an unknown prospect) than the exclusive, valued-customer offer I received in my inbox. Another annoyance is having a product ad chase me around different sites for days after I purchased the item in store.
Again, digital may seem cheaper and seemingly yield better results on the surface – but have ALL the costs really been considered? Are long-term results being overlooked for a quick win? In the case of brand reputation and customer experience the answer is yes.
You will always be my baby…
Even when you act like you don’t know me.
Recognizing a consumer when there are so many variations of an identity is challenging. Connecting all interactions and data available is key to offering a positive customer experience and improved business results. This is why you must have a pristine, single source of truth of your customers.
Data redundancies and inaccuracies impact the ability to gain a single view of the customer. Undeliverable and outdated addresses are important when it comes to direct mail for any company, but also as a component to matching to third party data. It is an identifier that drives accuracy across your marketing ecosystem.
An accurate, single view enables a clearer understanding of a customer’s value and needs in order to sell and service to her accordingly, deliver relevant messages – both online and offline, and continue to nurture the valuable relationship she has with your brand.
On the flip side, an accurate, single view helps protect you from connecting with consumers who are not likely to buy your product or services, previous customers that have a higher cost to serve than their value and those who have asked to opt out.
Play nicely with others.
Customer interaction and product data across channels and devices often gets stored in separate databases creating fragmented views of customers and inaccurate representations of their value.
If you aren’t already collaborating closely with your IT and Technical teams to break down the data silos, now is the time to start. Make sure they understand your specific data needs.
In addition to working together internally, a brand’s data must work with other companies’ data and analytics in order to bring relevancy, context and efficiency to all marketing efforts.
It’s not rocket science.
It’s data science. And it’s a BIG deal.
The average brand collects and analyzes data in some capacity with an eye on data quality.
Leaders are extending the value of offline data warehouses by connecting to an environment where personally identifiable information can be made anonymous and brought together with anonymized online data in a privacy safe way, enabling brands to analyze cross-channel marketing activities, perform closed-loop measurement, refine audience models and segmentation, map customer journeys and much more.
As a data geek this is wildly exciting, but remember our good buddy, GIGO and act accordingly. The value of the insight derived from big data is only as good as the quality of the data input.
Money doesn’t grow on trees.
Stop wasting it.
The business impact of poor data quality and inaccurate consumer recognition is significant. Redundancies increase marketing costs for no revenue return. Inaccuracies negatively impact conversion rates and revenue. The risk of deriving business decisions based on inaccurate data can prove costly in terms of misdirected marketing resources and damage the brand.
Change the world one day at a time.
How does your company measure up when it comes to data quality and consumer recognition capabilities? If you are not where you want to be, don’t try to change the world all at once. Pick one or two areas that make the most sense for where you are and take action. Don’t get too big for your britches when your colleagues start to follow your lead.