Personalization and precision marketing: Revenue streams in CPGs through AI


There is no denying that Artificial Intelligence is revolutionizing the business landscape in almost every industry. With the advent of new possible applications and the ongoing process of improving existing ones, AI is opening up exciting opportunities for those ready to take them. One key trend in this industry is personalization and precision marketing, which allows companies to improve their marketing efforts. According to Mckinsey, “Personalization can deliver five to eight times the ROI on marketing spend and can lift sales by 10% or more.” But with the average person in the US receiving 4000-10000 ads every day, it’s quite challenging to attract and retain a consumer. And in fact, customer acquisition cost (CaC) increased by 60% from 2014 to 2019. So, how do you stand out in this fiercely competitive market?

Leveraging personalization and precision marketing to build and nurture loyalty and drive sales

Many global CPGs have not been able to decode the key to a successful data-driven marketing effort. High-quality data has not been a problem for CPGs lately, most companies have started using AI data quality management tools to cleanse, standardize, and harmonize their deluge of data. The problem lies in how these data are used for marketing and promotion.

Traditional personalized marketing, comprising 14% of the entire marketing budget, is often targeted for a particular segment of the campaign. Yet, this has failed miserably as consumers (directly and indirectly) reject brands’ approach. According to a recent Gartner study, 80% of such personalized marketing efforts will be abandoned by 2025. This is mainly because of a lack of RoI and challenges with customer data management.

The need of the hour is having granular, precise, and scaled marketing across the spectrum of an enterprise that delivers a precise message to the right audience, at the right moment, and at the right place.

How to accomplish this?

Personalization through precision marketing is the new talk of the town that can be built using advanced CPG analytics, AI, and high-quality data. With a continuous feedback loop, the precision marketing model can predict demand, adjust marketing campaigns, and provide recommendations.

But what is precision marketing?

  1. Precision marketing focuses on outlining specific target segments and audiences in a very detailed manner.
  2. It relies on customized advertising messages tailored to the needs and wants of the target audience
  3. These messages can be updated in real-time according to the audience’s response

Marketers face many challenges when it comes to personalization. This strategy requires an enormous amount of high-quality data to be analyzed in real-time and decisions to be taken fast.

AI in CPG: unlocking new revenue streams

The integration of AI in businesses’ marketing efforts is pivotal to succeed in the actual competitive scenario. AI-powered systems can provide the solution to many of the challenges we discussed previously.

The look-alike modeling approach: targeting with AI

In economic terms, the most cost-effective approach to finding new customers is looking at the existing base. As explained by the Customer Data Platform Institute, by identifying top customers and applying the look-alike modeling (LAM) method, businesses can “target audiences who share similar characteristics, attitudes, and behaviors to their highest-value customers. By analyzing a broad selection of metrics, look-alike models create consistently evolving profiles that help businesses predict the customers who are most likely to be receptive to a product or service.”

This proves extremely valuable when it comes to identifying the right target audience for your campaign and online content.

AI for Data Discovery

Data have never been more accessible, but this doesn’t mean it’s easy. As stated by TechTarget, the risk of losing time and money on non-relevant data while missing the useful one is real. “Collecting data that isn’t needed adds time, cost, and complexity to the process. But leaving out useful data can limit a data set’s business value and affect analytics results.”

The automation of data collection plays an important role in reducing human error and dramatically decreasing processing time. This trend doesn’t involve only quantitative data. According to Google predictions, by 2031 we will see a 50% automation of all qualitative data collection.

Automated Decision Making

Once data are collected and analyzed we are confronted with maybe the most challenging step: decision-making. And decision making should be an ongoing process to update the marketing strategy in real-time according to customers’ responses.

Advanced analytics models are the core of automated decision processes. Through the designing of propensity scores, these models rate the probability of an individual or target reacting to a specific message or content. Propensity scores are constantly updated according to actual customer behavior: the target audience’s reaction towards the campaign is collected and tracked.

Propensity scores inform automated decision-making. Companies can decide to leave specific cases to management, but McKinsley recommends these exceptions to be below 5%.

Customer Data Platform (CDP)

To be useful for decision-making and strategy-building, data need to be aggregated. This allows companies to see all available information in one place: data about the target audience (demographic and behavioral information), and also data from all devices used by the audience.

This holistic and cross-channel approach is made possible by customer data platforms, and advanced software that stores first-party data and third-party data. And integrating AI into your CDP can uncover the real potential of customer data. Transforming massive amount of data into small, useful bits of information make the marketers’ job easier, allowing them to run data-driven campaigns, have access to strategic insights, create valuable content and distribute it through the correct channels to the right audience.

Gain competitive advantage through CPG Data Insight

It is clear that Artificial Intelligence will continue to play an increasingly important role in the future of marketing, especially in the CPG industry. AI-powered CPG data analytics can help companies achieve a data-driven method for marketing, meaning reducing human error margin, increasing revenues, setting more precise KPIs and goals, and better-allocating resources.

Companies like Tredence harness the power of AI to bring you closer than ever to your customers through data analytics, providing you with insights to build valuable long-term relationships with your audience.

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