LIMRA AI HANDS-ON SESSION

AI in Action: 5‑Step Guide for Marketers How to use AI for Segmentation,Targeting & Positioning What you need before you get started Your audience data A clear campaign goal Platform access (e.g., Copilot, ChatGPT, etc.)

Questions?

Contact Jonathan Yoon at yoonj2@nationwide.com Mary Crean at mfalletticrean@nfg.com

Common Mistakes to Avoid Overloading the model with too much data at once Using unclear FP definitions Asking for outputs before defining targeting

AI in Action: 5‑Step Guide for Marketers How to use AI for Segmentation,Targeting & Positioning Step 02-Segment your Financial Professionals (FPs)

Step 01-Load the dataset into AI

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First, give AI a persona: Tell the AI who you are and what context it’s working in.

You are an expert Marketing Strategist in Financial Services. You are especially experienced with Segmentation, Targeting, and Positioning.

Second load the dataset into AI:

Third, try a Prompt: Can you perform a simple exploratory data analysis and show me any interesting insight you find?

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What is it: The process of dividing a broad market into smaller, more defined groups of customers who have similar needs, characteristics, or behaviors.

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How AI can supercharge it: AI is great at detecting hidden patterns. It can analytically identify similar groups and cluster them. It can group by attributes it detects in its analysis, or by attributes that you provide in your prompt.

Sample prompts: Cluster FPs into 6 segments using CHANNEL, REGION, REVENUE_12MO, DIGITAL_ENGAGEMENT_SCORE, PROD_ (encoded), and wholesaler touchpoints. Name each segment and describe differentiators.”

Step 04-Draft content

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Step 03- Find target FPs for your campaign

What is it: Creating personalized messages to define how the chosen target segment(s) perceive the brand, product, or service relative to competitors.

How AI can supercharge it: AI can quickly tailor outreach for each FP. It can also make different messages depending on firm affiliation or product focus. AI can even provide omnichannel cue. Some examples include: Email copy Landing page variation Social ad formats These are common marketing outputs.

Sample prompts: 1. For each segment, draft a positioning statement and three message bullets. Tailor language for FPs in CHANNEL and top PRODUCT_MIX combos.

2. Map each segment to one primary and one secondary channel tactic (email, events, portal content, wholesaler outreach) with concrete CTAs.

What is it: The process of evaluating the potential and attractiveness of each segment identified during segmentation and then selecting one or more segments to focus the organization’s marketing efforts on.

How AI can supercharge it: AI can make predictions about the likeliness of a sale or an adoption of a product. AI can also do the opposite and identify firms/FPs with low adoption of products and give recommendations to engage.

Sample prompts: 1. Rank segments by potential for FIA adoption using FIA_PROPENSITY, average REVENUE_12MO, and engagement.

Return a table with segment size, mean propensity, mean revenue, and top three targeting levers.

2. Estimate lift if we focus on top two segments and increase WS_MEETINGS by +1 and EMAIL_OPEN_RATE by +5 pp. Simulate expected change in FIA_PROPENSITY.

Bonus-you can create a predictive model using AI

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First Build the model: Build a predictive model using this dataset. I will apply this model against a new dataset to find which FPs are likely to engage with marketing campaign.

Second Load new FP data into AI:

Third Use model to predict:

Here is a list of 100,000 new FPs that have not done any business with our company.

Return a list of Top 5,000 FPs based on probability to engage with marketing campaign.