Data Activation Guide: Redefining the CDP

When first-party data from across your business is unlocked and accessible, you can use Data Cloud's advanced segmentation to find high-value audiences. For example, you can create segments of customers with a high average order value, above average email engagement, infrequent returns, or an affinity for a category of products.

By targeting relevant customers with relevant promotions, you’ll reduce cost per acquisition since they will be more likely to convert. And with sales having access to all the same information as marketing, both teams can more easily build on each other’s work to ensure conversions are relevant, contextual, and effective.

In addition to advanced segmentation that helps you target high-value customers, you can also use AI and agents to help you increase efficiencies. Here's how it’s done in Data Cloud:

• Use AI agents to help you create target audience segments in minutes. With Data Cloud and Agentforce working together, you can simply describe the target audience you want, and the agent uses large language models (LLMs) to translate prompts into the appropriate segment attributes without requiring SQL.

• Use AI-powered lookalike modeling through ad platforms like Google, Meta, and others to identify customers most similar to high-value audiences to expand campaign reach.

• Measure the effectiveness of historical and in-flight advertising campaigns using AI to analyze and visualize the data to help you understand best-performing audiences and inform future activations.

Once you’ve created and optimised your target audience segments, it’s time to send that data to your ad platform of choice and activate it. Here’s what that can look like:

• Seamlessly and securely activate new audiences to walled garden platforms like Google Ads, Meta, Amazon, and LinkedIn then reach customers with personalised ads on their channel of choice.
• Widen your reach and further enrich your dataset using AppExchange partners like LiveRamp, TradeDesk, Merkle, Epsilon, and Axiom. Use segment-level insights directly from ad partners (like Google and Amazon) to understand customer affinities and demographics that can be used for future campaign personalisation.

Improving return on ad spend is not only about improving or expanding your target audiences. It’s about relevancy, timing, and knowing when not to send someone an ad. The combination of these things will save you money and also improve customer satisfaction. You should suppress ads when:

• A customer has an open service ticket.
• A customer purchased a product or service that’s now discounted.
• You’re promoting a loyalty program and the customer is already a member. You don’t need to waste their time engaging them with redundant offers.

You’ve got your data in order. Now you can use AI to:

• Understand highest value segments and their likelihood to respond to promotions.
• Determine next best actions or offers up for discussion to inform web personalisation.
• Help sales reps understand top opportunities for up/cross-sell, determine which contacts need follow-ups, and generate discussion points based on previous engagements.

Once you’ve ranked your audiences and identified the next best offers, you can:

• Create a Waterfall segment to nest and prioritise high-value audiences. Avoid marketing oversaturation by ensuring each customer only receives one tailored offer and doesn't receive messages about an item they just purchased.
• Use an AI agent to autonomously put customers on the highest priority journeys before they become oversaturated with messages and suppressed from promotions.
• Activate segment(s) for personalised content/recommendations on your website and move them into connected journeys on preferred channels that drive toward conversion.
• Synchronise data in third-party systems like POS, ERP, PIM, etc.
• Trigger notifications to sales and marketing teams to inform them of customer progress through a given journey and provide personalised recommendations on how to follow up to move toward a completed action (abandoned cart → purchase, finish application, etc.)
• Notify marketers about progress toward campaign outcomes and provide opportunities to intervene (like changing audience segment size or attributes, or tweaking the offer).

You’ve got your data in order. Now you can use AI and agents to:

• Create a segment of customers with a product utilisation score determined by an AI-powered calculation.
• Build calculated insights (propensity to buy score, lead score) to feed into AI-powered next-best-action recommendations so reps know exactly what kind of cross/up-sell opportunity to discuss with customers.
• Generate personalised sales follow-up emails with personalised copy and promotions included.
• Use an AI agent to capture contact info needed to make personalized recommendations, register a customer for a webinar, provide a gated asset, or schedule a follow up with a sales rep.

Once you’ve built your segments and calculated insights, you can:

• Enrich CRM objects (such as Contact or Opportunity) with unified data, giving reps access to the same unified customer profile information as marketing, service, and commerce teams, with the full context of every customer-brand interaction.
• Activate segments to your marketing engagement platform for personalised upsell/upgrade journeys.
• Trigger alerts in Slack generate talking points and BASHO email templates for reps so they can do targeted customer follow-ups.

You’ve got your data in order. Now you can use AI and agents to:

• Ideate on metrics, like predictive scores that can indicate when a customer is lagging behind in product adoption. You can also receive personalised recommendations on how to communicate with customers in order to drive to relevant resources and actions.
• Create segments of customers with low onboarding success scores (determined by AI-powered calculated insights), indicating they did not complete product onboarding steps or hit critical usage metrics within a specified time.

Once you’ve identified the right metrics to track and simplify your onboarding, you can:

• Activate segments to your marketing engagement platform (email, mobile, ads, web) for personalised education journeys with content offering support or to drive towards a critical action/next step.
• Follow up via your marketing engagement platform with personalised success journeys such as, recommended help articles, online help centre personalisation, etc.
• Trigger notifications to service and customer success teams (account, product health changes, service cases opened, customers at-risk of churn).
• Notify marketers about progress toward campaign outcomes and provide opportunities to intervene.

You’ve got your data in order. Now you can use AI and agents to:

• Help sales, service, and marketing teams develop communication to customers, explaining options to them (replacement or refund, chat with a service reps, watch a tutorial) with personalised recommendations or tailored offers based on previous engagement.
• Access a summary and recommendations on how to engage during inbound calls and provide next best actions or offers based on different customer segments.
• Use unstructured data, like knowledge articles or past high-performing marketing emails, to generate personalised communications for customers.
• Use AI agents to autonomously recommend and launch promotions to
  re-engage customers using propensity to churn scores.

Once you’ve used AI to help generate personalised communications, you can:

• Create an audience segment of customers who, for example, are impacted by product recall and have a high likelihood to churn/return a product, so you can proactively notify them.
• Use triggered flows to automatically create a case in Service Cloud for impacted customers.
• Use service data to create suppression segments/criteria so impacted customers are excluded from promotional emails or ads while they have open service cases.
• Create a trigger/action to close resolved service cases automatically and trigger a marketing journey to send out an email with a feedback survey.