Five behaviors that can lead to digital hoarding and how you can overcome them.
For many, "spring cleaning" means cleaning out closets and garages, but this is also an ideal time of the year for online marketers to assess their data landscape to find areas that have become drab and dusty. This time of year fits nicely between the post-holiday lull and pre-holiday planning phases, giving you ample opportunity to identify and resolve ways to clean up your data structure for the rest of the year.
Let's look at five behaviors that can lead to digital hoarding and how you can overcome them.
Accumulating massive amounts of data "in case of emergency." The slope to "data overload" and "big data" clutter is slippery. Before you know it, your email service provider, site analytics, and commerce platform databases can swell to hundreds of columns of data that, even if they overlap across partners, may differ in the details. While some data points need to exist within their native environment and others need to be exported, focus on two areas to decrease the clutter:
Streamline the data exchanges between databases to only share data that has a specific purpose. Do you need orders from five years ago in your email database? Additional data points can typically be added to these data exchanges without the custom work and development of day's past. Share only what you know you will use for segmentation, personalization, dynamic content, and reporting purposes.
The number of "in case of emergency" data points in your databases is just a stack of newspapers going back to the '90s. Even if you think your database is slim, there are fields that you can eliminate to make your data processes more streamlined, efficient, and quicker to access. Do you actually use middle initial, username, or a full postal address in your promotional emails?
Fear of losing something important. It's easy to overlook legacy data processes that are collecting cobwebs in your database. "If it ain't broke, don't fix it," right? Well, those once groundbreaking strategies for grouping customers into shopping personalities like "Miss Penny McPincher" have long since been abandoned for better customer aggregation methods, yet the Miss Penny McPincher profiles may still be getting updated daily or just sitting there weighing down your database. I once worked with a client who stored data that was over a decade old and could only be used with a commerce platform they had long since abandoned. They simply could not let go for fear of needing something, even though technologically there was no potential to use the information. Not only is there a technology strain for useless data, but errors could be made if new team members misinterpret which data points are valuable.
Keeping detailed records of things that are no longer necessary. Whether your job is data-dependent or data-adjacent, at some point you have encountered a multi-page (legal size) database schema or architecture taped together and stuck on a wall. You probably have folders or printouts tucked away outlining various data approaches throughout the years. Talk to your partners and see if there is a way to generate automated reports that are more up to date, require barely any resources to create, and can be read digitally. You may understand (or have documented) the logic behind redundant or contradicting fields in your database like "ORDERDATE," "Order_Date," and "ORDER_MMDDYYYY," but this situation is a powder keg looking for a spark. One misstep by you or another team member could result in an email being sent in error or containing incorrect information.
Acquiring and holding onto items of little or no value. Facebook, Twitter, Instagram, Pinterest, in-store, etc. Your acquisition sources have exploded beyond your website and checkout process. Along the way you have likely asked customers to provide data that was specific to a promotion, contest, or other limited-time event. That data could be clogging up the spigot to useful data on their profile. Sure, asking Facebook likers to tell you their favorite color on a Facebook-hosted email opt-in form generated a lot of buzz and helped you showcase 2010's vividly colored product line, but how useful is that data to you now? Preferences change and so does your product line. Storing this information is not adding value to your bottom line or to the customer's experience.
Acquiring too much data. The last digital hoarding behavior is also the one I see most often. The excuse of "Oh, I just have too much data. I don't know where to start. I'll just let it all keep piling up" will get you nowhere. Actually, it will get you somewhere...buried. Yes, buried and stuck. As a marketer, you must understand what data you store and why. You must be able to articulate the value of the data for it to justifiably exist. Otherwise the walls will start to close in and you will throw your hands up and surrender.
Just like the television shows featuring compulsive hoarders, cleaning out years of clutter can require a team of folks to get the job started. Recruit members of your technology team, fellow marketers, and relevant partners to help establish your "keep" and "trash" piles rather than just slashing away on your own. Another critical part to the process is to modify your own behavior. While determining which pieces of data get tossed, try to understand how the data started piling up in the first place and what you can do to avoid repeating this behavior. Perhaps it's establishing a better process for handling data for short-term promotions like a Facebook contest or switching your list structure to match various acquisition sources.
So, go ahead, catch some spring cleaning fever and tidy up your data.
As an expert in email, mobile, and social strategies, Jim brings 15 years of experience in online marketing, managing email and cross-channel programs for top retail clients. From strategic vision to implementation, Jim has led clients to successfully meet aggressive revenue and performance goals. As Bronto's director of research, he regularly publishes industry-focused white papers, research reports, and contributes to the Bronto Blog.
IBM Social Analytics: The Science Behind Social Media Marketing 80% of internet users say they prefer to connect with brands via Facebook. 65% of social media users say they use it to learn more about brands, products and services. Learn about how to find more about customers' attitudes, preferences and buying habits from what they say on social media channels.