Cracking the Consumer Code with AI

Audience strategy is intricate, & AI, with DeepLimeSeg (DLS), is cracking its code. Explainable AI (XAI) isn’t a figment or segment of your imagination.

DLS segments your data and gives explanations on which factors contributed to the given cluster (e.g. high-value customers: buying habits, demo/psychographic factors, etc). This crucial framework is based on the tradeoff (λ) of accurate and explainable data.

- F(θ) = Accuracy(θ) − λ ∗ Explainability(θ) 
Here's an overview of how each contributes:

AI in Uncovering Audience Insights

   General AI technology plays a crucial role in analyzing complex audience data, revealing intricate patterns that are essential for crafting targeted marketing strategies.

DeepLimeSeg’s Role in Precision Segmentation

   DeepLimeSeg, leveraging DRL (Deep Reinforced Learning), XAI (Explainable AI), and LIME (Local Interpretable Model-agnostic Explanations), provides a detailed segmentation approach. In my opinion, the most valuable effect is identifying the superconsumers (SC) – a small yet incredibly influential audience segment.

- XAI: Explainable AI ensures our strategies are not just effective, but also understandable, allowing us to trust the decisions made by AI

- LIME: A technique we use to make our AI’s decision-making transparent and easy to interpret, ensuring we know exactly why certain marketing choices are being recommended

- DRL: Deep reinforced learning helps the AI learn from vast amounts of data, much like a human learns from experiences, to make smarter marketing decisions
 

Why Superconsumers Matter

  Here’s something interesting: 10% of your audience, the SCs, could account for up to 70% of sales. SCs play a critical role in driving 'share of growth'; understanding and engaging with this group can be transformative for brands. At Brainlabs, overlapping identifiers from SCs are often found in our most valuable audiences (MVAs).

Knowledge Graphs for Deeper Insight with DLS

   Knowledge graphs help AI see and understand the complex relationships between different consumer behaviors, giving us a 360-degree view of our audience. They can also help humans understand complex relationships - the below illustrates how brands can utilize AI, as outlined in this article.

 
 
Hypothetical Use Case Examples

 Banking and Financial Services:

- Scenario: A bank wants to increase the uptake of its new investment product among millennials.
- DLS Application: By analyzing transactional data, social media activity, and demographic information, DLS identifies a segment of millennial customers who are tech-savvy but financially conservative.
- Strategy: The bank develops a digital marketing campaign targeting this segment with educational content about low-risk investment opportunities, utilizing platforms where these customers are most active.
- SC Considerations: The identification of a segment of tech-savvy but financially conservative millennials is based on superconsumer behavior analysis. These individuals likely engage more with financial content online, indicating a deeper interest in financial products. The bank targets these superconsumers with educational content about low-risk investments, leveraging their existing interest to drive engagement.

Health and Wellness Industry:

- Scenario: A health and wellness brand aims to market a new range of organic supplements.
- DLS Application: The brand uses DLS to sift through customer purchase histories and online behavior, identifying a segment deeply interested in organic and natural products.
- Strategy: The company creates personalized email campaigns and social media content highlighting the organic nature and health benefits of their supplements, directly addressing the interests and values of this segment.
- SC Considerations: The health and wellness brand targets superconsumers interested in organic and natural products. These customers likely exhibit behaviors such as actively searching for organic products and participating in health-related discussions online. The personalized campaigns are designed to resonate with these superconsumers' values and interests, thereby enhancing engagement.

Education Technology:

- Scenario: An EdTech company seeks to promote its new AI-based learning platform.
- DLS Application: DLS analyzes user data from existing platforms, feedback forms, and educational forums, identifying a segment of learners who value personalized and flexible learning experiences.
Strategy: The company targets this segment with a content marketing strategy, showcasing success stories and user testimonials about the platform's adaptability and personalization features.
- SC Considerations: The EdTech company focuses on learners who value personalized and flexible learning experiences. These superconsumers are likely to be more engaged in online learning communities and platforms. By showcasing success stories and testimonials that align with their preferences, the company directly appeals to these superconsumers, increasing the likelihood of adoption.
Final Thoughts and Considerations 

   Outside of knowledge graphs, computation requirements can be mitigated through model optimizations, applying theories (Value Co-creation, TRA, TPB), time series forecasting models (ARIMA & LSTM), & customer journey mapping. In the process of AB testing which combination is most appropriate to reduce this - will share findings when this is completed!

#ReframingFramework #ArtificialIntelligence #CustomerSegmentation #DataAnalytics #ExplainableAI #MachineLearning #MarketingStrategy #Superconsumers #AudienceStrategy #XAI #AI #OpenAI

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Further context on DeepLimeSeg can be found from an article which within a special issue of Mathematics, “Mathematical Optimization in Pattern Recognition, Machine learning and Data Mining”, titled: A Mathematical Model for Customer Segmentation Leveraging Deep Learning, Explainable AI, and RFM Analysis in Targeted Marketing

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AIM - AI Marketing - a strategic marketing analyst with expertise in data correlation and audience development
 

On a separate note, I'd like to take a moment for a shameless plug about an tool I've developed – the AIM v1. This AI Marketing GPT, specializes in providing detailed, tailored marketing advice, identifying brand characteristics, analyzing market dynamics, and deeply understanding customer behavior. Whether you're crafting Ideal Customer Profiles or devising intricate marketing strategies, AIM v1 brings a unique blend of expertise in demographics, psychographics, shopper values, and media touchpoints. It's not just about suggesting effective marketing channels; AIM v1 dives into highly specific tactics within each channel, ensuring your approach is both strategic and practical. For businesses targeting specific segments, like B2B marketing to C-suite executives, AIM v1 is particularly adept.

  
As always, the content promoting AIM is written by AIM.

Any feedback for v2 is appreciated and will be considered.