Customer Data & Analytics Blog

Why Marketing Executives Should Care About AI: Part 2

Josh Fayer | 2 minute read

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Last week’s blog post focused on what AI is, what it can do within an organization, and its potential limitations. Today’s blog will talk about how you can go about finding the right technology for your business.

So you’ve done your research, you know what AI can do for your organization, and what its possible limitations are. You’ve found problems in your martech stack that you want to fix—maybe your data is siloed and it’s difficult to run a coordinated campaign, or marketing analytics are marred by human processing time and don’t scale well to the current size of your business. Whatever the case, you’ve decided to take the next step in integrating AI into your marketing stack.

The name of the game is ‘features’

It’s pretty self-explanatory: if a product doesn’t have the features to address the problems you’ve identified, it won’t help very much! There are a few key features you might want to look for—of course, in addition to an AI-powered analytics platform.

Automation

Depending on the size and bandwidth of your data science department, automation is a key feature of a CDP. Automation, specifically the usage of integrated AutoML, helps keep data management under wraps for any size of data science teams, and even enables team members with little to no training in machine learning to manage existing models—this group belongs to the newly-coined term “citizen data scientists.” For more information about AutoML, read our recent blog on the subject. In brief, AutoML removes the need for human intervention in the menial, repetitive, and time-consuming tasks behind machine learning.

Constant growth

There’s a point when you open your fridge at home and get hit with that “three week old leftovers” sensation—if you’re anything like me, after far too long you take this as a plea to clean out your leftovers, leave the good stuff, and remove everything you probably should have chucked a month ago. So, too, must you be diligent with your data. Running a campaign off of stale data won’t generate the same kinds of results as it would with fresh, up-to-date data. Your service should constantly be intaking new data, unifying it intelligently (not shoving duplicate records into the same database, for example) and enriching it from internal and external sources.

Make the data work for you

Your data platform should also be capable of finding interesting insights from the data you feed it. Next-generation customer data platforms are constantly improving their abilities in this category. Consider looking for a service that performs micro-segmentation to allow for high granularity of selective marketing, pattern discovery to help predict what your customers will do next, and marketing recommendations, to put the right content in front of the right audience. These insights are the core reasoning behind investing in a customer data platform, so make sure you’re getting your money’s worth!

Data is either your friend or your bottleneck

Of course, the prerequisite for all of this is a healthy, robust database. What kinds of data should you be collecting on your customers to produce insights, and what’s available to enrich what you already have? Stay tuned for next week’s blog, which will go into the steps required to find the right solution for your available data.

Josh Fayer manages Marketing Communications at Zylotech, where he brings an extensive background in public relations and computer science. Josh Loves music! He sings with an a cappella group, Orange Appeal, (whose recent album Unpeeled he shamelessly plugs at work), and at home he loves to mess around with a variety of instruments. Josh enjoys spending quality time with his adorable dog, and exploring around his new home near the South Shore of Boston.

If you liked this post, check out our other blog post about strengthening social media activities with customer data.

Topics: Customer Intelligence