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4 Ways AI Can Enhance Your Marketing Data

If you struggle with Robophobia, an anxiety disorder marked by an irrational (or rational in the event you’re at risk of being made redundant) fear of robots, drones, robot-like mechanics or artificial intelligence (AI), have we got some good news for you. The robots may be taking over the world, but this means they are also taking on all the things you loathe about marketing data quality management. That’s right, all the boring manual data entry and data management jobs that you and your marketing operations team spend countless tedious hours doing—the bots can knock it out in seconds without so much as a yawn or a creeping case of the Mondays. Best of all, you can take credit for all of their genius without the slightest twinge of guilt, cause unless you’re human (a.k.a. sentient), you really can’t feel it when a “co-worker” stabs you in the back.

I Like Big Bots and I Cannot Lie

And now, let’s talk about all the mind-numbing tasks you can fob off to the latest and greatest AI and machine learning technologies currently dominating the data quality improvement domain. These blessedly brilliant automated technologies have the power to automate and refine your marketing data, ensuring that you, your company, and more importantly, your marketing campaigns, are never in want of the most accurate, current, complete, enriched and relevant data. To help you figure out where you want to plug in (literally) a little help from your AI marketing data friends, we’ve rounded up four marketing ops tasks that benefit greatly from AI’s automated wizardry.

1. Use AI to Clean and Enrich Your Data

Whether your marketing data lists are comprised of 5,000 or 500,000 contacts, or more, the AI-driven algorithms used by modern marketing data cleansing technologies have the ability to:

  • Analyze vast datasets with lightning speed
  • Identify data anomalies and inconsistencies for your review
  • Correct costly data errors in real-time
  • Supply information missing from various fields using third-party data
  • Detect, merge and delete duplicate records
  • Normalize and streamline datasets according to the standards you set

As we mentioned above, AI can enrich existing data by appending relevant information from a variety of external sources (a.k.a. third-party data). For example, you can beef up your customer profiles by adding helpful information, like social media data, purchase histories, demographic details, and more. Enriching your data with this kind of information has a number of strategic advantages, including:

  • Improved Decision-Making and Strategy Development — According to Forrester, companies that use data-driven insights achieve an average of 8% higher year-over-year growth.
  • Enhanced Personalization and Customer Experiences (CX) — Epsilon found that 80% of customers are more likely to make a purchase when brands offer personalized experiences, resulting in increased customer loyalty and retention.
  • Better Targeting and List Segmentation — Mailchimp reports that segmented email campaigns have 14% higher open rates.
  • Increased Customer Engagement and Conversion Rates— Aberdeen Group maintains that companies with strong data enrichment strategies enjoy a 36% higher click-through rate.
  • Enhanced Fraud Detection and Risk Mitigation — PwC reports that 34% of organizations say fraud-related losses decrease when data analytics and enrichment techniques are used.

2. Use AI to Perform Predictive Analytics for Data Quality Forecasting

Leave it to the bots to find the proverbial needle in the haystack. AI-powered predictive analytics can detect patterns and anomalies in marketing data faster than a person or team of people ever could. As we mentioned earlier, when you use AI to identify and correct data errors, inconsistencies, and missing values, it improves the overall quality of your data. So, what does this mean for the future of your data or data quality forecasting? It means that you can use AI-enabled predictive analytics to anticipate, prepare for, and sidestep potential data quality issues.

By analyzing historical data patterns, machine learning models can forecast inaccuracies or data gaps. This allows your team to spend their valuable time taking proactive measures, mitigating risks and preventing future problems. In short, by forecasting data quality issues, businesses can allocate resources more efficiently to data management and marketing efforts. This leads to optimized resource allocation and a higher ROI on marketing campaigns, which is a win-win for everyone, bots and humans alike!

3. Use AI to Automate Data Integration

Marketing teams often have to deal with data spread across a myriad of cobbled together systems, platforms, and tools. Manually integrating this data is not only cumbersome and error-prone, it takes forever and leads to employee burnout. When you use AI-driven tools to automate the process of sharing, processing and integrating data across your enterprise, it empowers your people to focus on more exciting things, like:

  • Scaling personalized campaigns
  • Coordinating complex cross-channel campaigns
  • Enabling sales, thanks to integrated sales and marketing tech
  • Creating a compelling and cohesive customer experience

4. Use AI to Segment Customer Lists and Target the Right Audiences

AI-driven customer segmentation delivers a domino effect of pure goodness in that it first empowers you to divide your list or audience into distinct groups that you can make as broad or as narrow as you like. In our experience, the more narrow the group, the more personal and productive your campaigns will be. Moreover, if you use a data dashboard, you can see what’s going on with your data on a segment level in real-time. This, of course, is critical to your ability to respond to the insights, issues and opportunities your data reveals and discover and use more interesting segments based on behavior, personal preferences, demographics, etc. Because segmentation helps you to be more targeted (personal) in your campaign content, it leads to higher engagement rates, which produces greater conversion rates. Cue Charlie Sheen winning memes!

AI + Marketing Data Processes = True Love

When AI is used to automate marketing data quality improvement processes, it is a game-changer for you, your ops team and your business. Not only are you able to automate tedious tasks with AI-enabled tech, you can ensure your data is accurate, find invaluable insights faster and craft more effective and profitable marketing strategies. As for your human employees, embracing this dynamic duo empowers the peeps on your ops team to be more agile, proactive, and customer-focused in their efforts, which ultimately drives business growth and success.

In It to Win It

Sureshot has a long history of helping organizations use AI to get and maintain high-quality data that enhances the performance of campaigns and drives revenue. If you are ready to harness the power of AI + data to unlock the full potential of your marketing efforts, start by taking our FREE Martech Assessment.