6 Ways Gen AI Can Help You Build Winning Consumer Marketing Strategies

Generative AI

Date : 06/06/2024

Generative AI

Date : 06/06/2024

6 Ways Gen AI Can Help You Build Winning Consumer Marketing Strategies

Discover how generative AI revolutionizes consumer marketing with hyper-personalization, real-time insights, and efficient omnichannel strategies for increased engagement and ROI.

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6 Ways Gen AI Can Help You Build Winning Consumer Marketing Strategies
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6 Ways Gen AI Can Help You Build Winning Consumer Marketing Strategies

Table of contents

6 Ways Gen AI Can Help You Build Winning Consumer Marketing Strategies

6 Ways Gen AI Can Help You Build Winning Consumer Marketing Strategies

Consumer marketing, at its core, is simple. It is all about putting the right offer in front of the right customer through the right channel, but that’s easier said than done. Because what works for a segment of customers might be completely different from what another wants. Even more so when the demanding modern consumer is emerging as a segment of one, and behavioral data is notoriously hard to aggregate and analyze. This is why generative AI, with its key capability of mining structured and unstructured data to surface real-time insights, is set to emerge as a disruptive force in consumer marketing. 

Gartner forecasts that by 2025, 30% of outbound marketing messages from large organizations will be generated using generative AI, up from only 2% in 2022. Here is a look at the transformative impact gen AI will have on consumer-centric marketing. 

How Generative AI is Reshaping Consumer Marketing:

Segmenting Your Customers:

Every marketer knows that the first step before crafting a marketing plan is to segment customers. Treating all of your prospective customers with the same yardstick is an easy ticket to low conversions and full-blown disappointment. 

This far, consumer segmentation has largely used traditional techniques that harness conventional data like market research studies and sales figures to create static segments that could be relevant within months if not weeks, negating returns on time and effort. Generative AI algorithms resolve this bottleneck since they can interpret regular data sources, unstructured data such as media coverage of category trends and competitor moves, and social media sentiment as well as the tribal knowledge of your marketing teams, to create segments that have two strengths. They are unique rather than generic and can be refined in real time to maximize returns both on your initial investments as well as your marketing costs.

“We'll be able to ask questions we could never ask before, and we could get the answers faster” 

As gen AI evolves, Strategic Advisors in AI & Digital Transformation
Dr. Rod Fontecilla told TechTarget that it would layer more data into the segmentation analysis, helping to bring even more granularity to the process.

Source: TechTarget

Hyper-personalizing Customer Journeys to Build Customer Loyalty and Shape Strategy

Once you have your segmentation and strategy in place, it is time to use them as a foundation to engage with customers. For this, you have to build journeys spanning different components of the customer lifecycle, such as attracting, retaining, cross-selling, service, and so on. A highly optimized customer journey has to ensure low levels of churn, smooth, seamless experiences, and higher Customer Satisfaction (CSAT) scores. Broken customer journeys will affect your customer experience and drive customers to the competition. 

Just as in segmentation, earlier techniques of journey building are falling short as customers behave more unpredictably than ever before. Again, this opens up an opportunity for a generative AI use case. Instead of relying on historical data alone, generative AI’s algorithms trawl conventional and unstructured data to identify changing customer requirements and opportunities to differentiate and personalize in near-real time, effectively creating a segment of one. This can significantly boost journey optimization to deliver improved retention and loyalty. The live data can also be used to continuously refine the organization’s customer experience frontiers and other activities.  

Tapestry, the parent company of major fashion brands like Kate Spade, uses gen AI to personalize marketing copy based on which words and phrases perform well with specific buyers and adapts customers’ cart checkout experience to their browsing behavior and preferences.

“Gen AI-driven personalized paths can reduce cart abandonment and deliver a 3% to 5% increase in e-commerce revenues.”

Source: eMarketer

Creates Content for Your Consumer Marketing Campaigns:

Hyperpersonalization of content places a persistent additional demand on your technology and manpower. Thankfully, this is an application for generative AI. From a single brief, the technology can generate everything from social media copy to high-quality video ads personalized for a segment of one. With suitable generative AI algorithms, creating and personalizing marketing and branding material, product descriptions, visual ads, product demo videos, and personalized jingles - tasks that would have taken days, if not weeks, especially from a customization standpoint will get done in minutes.

In mid-2023, cruise line Virgin Voyages leveraged generative AI so customers could customize cruise booking invitations. The campaign featuring J. Lo’s digital twin, “Jen AI,” had highly personalized interactions with every customer who clicked through, closely mimicking the star. According to the company, the highly successful campaign had higher engagement rates than earlier ones, bringing in over 1,000 bookings.

Source: CNBC

Effective Omnichannel Marketing

Further complicating modern marketing engagement is the plethora of channels. As customers flit across channels throughout their journeys, companies are at risk of delivering experiences with greater friction. This happens when the customer has to repeat themselves or is engaged in a manner they do not prefer as they traverse channels. Like Disney and Sephora, leaders in their spheres already use AI to personalize their omnichannel engagement. Gen AI can elevate this by rapidly tracking individual and larger behavioral data that feeds into a live, unified customer 360 to ensure an omnichannel experience that is even more seamless and contextually engaging. 

Increasing the efficiency and RoI of marketing operations

From interpreting the findings of A/B testing to helping teams ideate, create and personalize on the go, to tailoring journeys in real-time, generative AI can leverage its central capability of marrying conventional and unconventional, historical and live data to deliver highly usable insights. With all marketing activities done faster and delivered more effectively, teams will be freed up to innovate, and metrics such as retention and conversion will see a sure uptick.

Marketing productivity alone due to gen AI could increase between 5 and 15 percent of total marketing spending, which is worth about $463 billion annually.

Source: McKinsey

Cascading consumer insights across the organization

Marketing, sales, and service know the customer deeply and have always shared their wisdom with each other and other functions across the business. A combination of generative AI and automation is now set to make these exchanges smoother and more impactful on the bottom line. For instance, a direct-to-consumer retailer leveraged generative AI to engage contextually during each service interaction. The algorithm retrieves necessary information from across business functions, makes changes for greater personalization, and delivers them in the brand voice. McKinsey found that this deployment of gen AI delivered an 80 percent decrease in time to first response and a four-minute reduction in average time to resolve a ticket.

The Competitive Advantage of Proprietary Data

Undoubtedly, the practical applications of gen AI will spawn a new wave of customer engagement that will transform the brand-customer dynamics. As this becomes table stakes, McKinsey asserts that the businesses that will pull ahead will be those that train off-the-shelf generative AI algorithms with proprietary data. To maximize returns, you also need to decide if parts of your current tech stack can be leveraged or need to be upgraded for these algorithms to fuel winning strategies. Let us help you superpower your generative AI arsenal for consumer marketing. 

Editorial Team

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Editorial Team
Tredence

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