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The Value of Artificial Intelligence in Customer Data Platforms

In this special guest feature, Aditya Bhamidipaty, Founder & CEO, FirstHive, discusses how businesses today face an expanding gap between the value their customers’ data can potentially provide and the true value their CDPs can create. AI systems can help close this gap by enhancing the productivity of human workers, so long as those workers are trained how to use those systems effectively. Aditya has been a serial technology entrepreneur solving problems for marketers. His stewardship has helped FirstHive to carve a name for itself in the marketing technology industry, delivering ROI to some of the world’s largest brands on their marketing initiatives.

The role of marketing is synonymous with the notion of customer data. In today’s hyper-digitized world, having the ability to gather customer data and analyze it via customer data platforms (CDPs) is vital for businesses to remain relevant and successful. Although, between an increasing amount of interaction channels, organizational roadblocks, ever-growing competition, and heightened customer expectations, marketers are often handed greater quantities of data than they can use efficiently.

In order to use customer data effectively, marketers must lean on the resources available to them in assembling and converting customer data into unified profiles, analyze patterns in those profiles, implement customer treatment solutions, and continually measure the performance of those solutions. However, each of these steps is limited by the bottleneck of human labor. As such, marketers have come to rely on artificial intelligence (AI) to perform these tasks in a way that provides value to both their organization and its customers.

AI is faster and more cost-efficient than traditional labor

Utilizing AI technology in CDPs grants increased processing speeds at lower total costs to organizations, but often still relies heavily on the knowledge and skills of experts to set up and maintain in perpetuity. Due to both the variety and volume of customer data, marketers have to generate and analyze and simply employing additional staff isn’t a realistic solution. The opportunities for organizations to improve their customers’ experiences based on the data they gather and analyze tend to grow much faster than they can afford. As such, the best way for companies to maintain and improve their CDPs is through applying technologies like AI to complement the productivity of their staff.

Using AI systems in CDPs poses a number of benefits to organizations. AI is able to assemble customers’ source data, classify and file that data, and recommend how it should be mapped into existing CDPs, converted into structured customer profiles, and analyzed to find isolated and common inputs and outputs alike far quicker — and in larger amounts — than manual labor can provide. From there, AI systems can simplify the unification of customer data, eliminate guesswork and risky experimentations, also greatly reduce manual dependencies across various verticals like IT, Data & Marketing

Overcoming the challenges of AI in CDPs

The only caveat in using AI with CDPs is that AI is still limited in its output functionality. While AI does allow marketers and their organizations a competitive edge in keeping pace with their customers’ data, workers must routinely review the performance of their AI systems to overcome the challenges associated with its use and integration with their CDPs.

For example, AI systems might need to be trained to collect additional data points human workers would know to collect, such as whether a specific customer interaction occurred after business hours. It may also need to be structured to mitigate the complexity of its algorithms to best meet the needs of the organization and its CDPs. Additionally, it may require workers to list the most valuable inputs of customer data so that outlying figures can be flagged or excluded. Furthermore, AI systems may not always come equipped with features that allow workers to visualize unmet needs or gaps in a certain CDP. 

As valuable as AI is to building and maintaining CDPs, the ability for organizations to reskill their workers to best understand the performance and limitations of their AI systems is just as valuable. Because the realm of AI is constantly evolving, workers must be trained on how to utilize these systems in order to best meet the needs of their organizations, their customers, and their CDPs.

Final remarks

Businesses today face an expanding gap between the value their customers’ data can potentially provide and the true value their CDPs can create. AI systems can help close this gap by enhancing the productivity of human workers, so long as those workers are trained how to use those systems effectively. The organizations that are able to accomplish this will ultimately thrive. The ones that don’t will struggle to keep up with both their customer’s needs and competitors.

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