Personalization is no longer a nice-to-have for today’s marketers — it’s a necessity. According to McKinsey, 71% of customers expect personalized experiences. If you don’t provide seamless experiences for your customers, they’ll leave you for a brand that does. The best way to deliver exceptional experiences is to capture rich data about your customers’ needs and preferences so you can understand them on a deep level.
However, recent changes in the data privacy landscape have made it more challenging for brands to capture insights about their customers. Regulations like GDPR and CCPA — as well as tracking restrictions on Chrome, Firefox, and Safari — have limited third-party cookie tracking, a prime source of customer data. As a result, brands are scrambling for a workaround.
Cutting-edge marketers are supplementing this loss of third-party tracking with first-party data, or data that customers have willingly shared with their brand, such as website interactions, online chats, social media mentions, purchase history, phone conversations, and more. The issue with first-party data collection is that it is often manual, and marketers need to synthesize data from a wide array of sources.
That’s where AI comes in — with this powerful technology, marketers can capture first-party data more effectively than ever before and at scale. Think about it — every website click, email open, contact center call, and in-store purchase contains valuable signals about what customers want. AI can process all these touchpoints at once and spot patterns that humans would never catch, building rich profiles based on real engagement rather than breadcrumbs.
Keep reading to learn how you can use AI to build more complete customer profiles and power more effective personalization as a result.
What Is a Customer Profile?
A customer profile is a comprehensive digital representation of an individual customer. Customer profiles combine multiple cross-channel data points to create a detailed understanding of who they are, what they want, and how they behave.
The power of modern customer profiles comes from their dynamic nature — they continuously update as customers interact with your brand across channels. When implemented effectively, these profiles enable deeply personalized experiences like showing product recommendations based on browsing patterns, tailoring content to specific interests, adjusting messaging tone to match communication preferences, and even anticipating needs before customers express them directly.
What data do you need to create a customer profile?
Here are some of the data points your business can collect in order to create a thorough customer profile:
- Website engagement: Page views, product browsing patterns, content preferences, search queries, session duration, abandoned carts, form completions
- Phone conversation insights: Products discussed, questions asked, objections raised, sentiment expressed, conversion outcomes, call duration, agent interactions
- Email engagement: Open rates, click patterns, preferred content types, optimal send times, promotional responsiveness, forward/share behaviors
- Mobile app behavior: Feature usage, in-app purchases, notification responses, session frequency, user journey flows, time spent in different sections
- Purchase history: Transaction values, product categories, purchase frequency, seasonal patterns, cross-category purchasing, promotion responses
- Customer service interactions: Support tickets, chat transcripts, issue types, resolution satisfaction, preferred support channels
- Social media engagement: Content interactions, comments, shares, sentiment expressed, response to different content themes, participation in brand communities
- In-store/physical location data: Visit frequency, dwell time, departments visited, in-store purchases linked to digital profile, associates interacted with
- Surveys and feedback: Direct input on preferences, satisfaction scores, Net Promoter Scores, product ratings, improvement suggestions
When combined, these diverse data sources create a 360-degree view of each customer that you can use to fuel personalization.
Enrich Your Customer Profiles With Conversation Analytics Insights
Capturing first-party data from the thousands of phone calls your organization receives every day can seem like a daunting task. Your team doesn’t have the capacity to listen to all those calls, let alone identify the common trends that are occurring in conversations.
That’s where conversation analytics AI comes in — with Invoca, you can let AI do the listening for you. Invoca's platform can automatically transcribe and analyze phone conversations to identify key topics, outcomes, and insights. This includes information such as the products or services discussed, the customer's intent, and if they faced any barriers to purchase. Invoca’s AI automatically identifies trends at scale, so you can understand your callers’ needs. From there, you can drill down into each topic to get more detail and see specific instances where it was mentioned.
The next logical question is, “How can I use these insights in my existing workflows?” Don’t worry, Invoca turns conversation signals into structured data and pushes them into the martech platforms you use every day, including Salesforce, Google Ads, Adobe Experience Cloud, Search Ads 360, as well as your customer data platform (CDP).
Easily Train Custom AI Models to Unlock Insights from Phone Conversations
Training an AI model may sound difficult, but not with Invoca! Signal AI Studio has a no-code UI that speeds you through the process of training a custom AI model. You simply tell it the insight you want to measure, and Signal AI Studio shows you transcribed examples from your calls that either fit or don’t fit that insight. It learns with every response, creating a new AI model in no time.
Custom AI models from Signal AI Studio can accurately detect virtually any insight or topic from conversations, including:
- Caller intent: Detect if the caller is a sales lead, current customer, new or existing patient, or job seeker
- Caller interest: Determine the specific product or service the caller is interested in, if they are looking for help with an online order, or need support with a product issue
- Conversation outcome: Detect if the caller made a purchase, booked an appointment, received a quote, or canceled a service
- Call events: Discover important events, like if the caller asked to be called back or to speak to a supervisor
- Voice of the customer (VoC) insights: Detect if the caller asked about pricing or a specific product feature, discussed a competitor, or lodged a complaint
You can use this tool to capture deep insights about your customers to build stronger profiles.
Learn more about how Signal AI Studio works here
Identify Phone Conversation Themes with Signal AI Discovery
It can be challenging to sift through your mountains of voice-of-the-customer data to identify trends. That's where Invoca Signal AI Discovery comes in. This tool allows you to visualize the themes and related topics being discussed across thousands of your calls at once to surface unexpected insights. You can specify the topics or categories you want Signal AI Discovery to visualize, view GPT-powered descriptions of topic summaries, and review transcribed examples from actual calls. Signal AI Discovery is a unique and powerful way to surface new and actionable insights on customers, call experiences, agent performance, and digital marketing campaigns that you may not think of looking for.
This surfaces previously unknown insights that give you a deeper understanding of what your customers are interested in and how to target them.
Track Customer Sentiment to Address Issues and Improve Customer Experiences
Another key piece of a customer profile is sentiment. This can be critical for future remarketing efforts, as it's clearly more effective to target satisfied customers with upsell campaigns versus frustrated ones.
When it comes to analyzing customer sentiment, most speech analytics tools only track the overall sentiment of a single call, flagging a call as either “positive” or “negative.” But many marketers say that looking at sentiment on an individual call isn’t always useful or actionable. We believe the real opportunity lies in the ability to track sentiment over multiple calls, so marketers can evaluate trends over time. That’s why Invoca makes it possible to monitor sentiment at scale, so you can correct customer experience issues and adjust your strategy accordingly.
3 Ways Marketers Use AI Customer Profiles to Drive More Revenue
Now that we’ve covered the basics, let’s dive into how leading brands use their AI-fueled customer profiles to drive more revenue from marketing campaigns.
1. A Leading Telecom Company Uses AI to Improve Ad Targeting and Lookalike Audiences
Most of this leading telecom company’s marketing budget goes to Google paid search. However, before using Invoca, it didn’t have visibility into the phone call conversions each campaign, ad, and keyword drove. Since many of its customers buy over the phone, this was making it difficult to understand which campaigns were truly returning the best ROI.
The telecom company used Invoca’s AI to understand not just which customers converted over the phone, but the average value of the conversion for each customer type. With this data,it could understand the revenue that each paid search campaign, ad, and keyword drove — both online and over the phone. It could then feed this revenue data into Google Ads to inform Smart Bidding. Smart Bidding weighs bids in proportion to their returns, decreasing their cost per acquisition by 82% in a two-year period. It also achieved an 18% lift in net revenue from paid search.
To replicate and scale their results, the telecom company uses Invoca to build lookalike audiences. Invoca’s AI automatically identifies the most valuable callers who made a purchase — the team then feeds these audience members back into their martech stack to find similar people who have a high probability of purchasing. This has been a valuable tool to help them expand their reach.
“The results with Invoca have been phenomenal, to say the least,” said the senior manager of search engine marketing. “The benefits are constantly compounding with such minimal lift for the returns. I’ve never had a product where I spend more time selling people on the results than doing the work to get it going.”
2. Banner Health Uses AI to Personalize Marketing for New vs. Existing Patients
Banner Health runs a wide array of digital marketing campaigns to drive appointment calls to its contact center. To optimize media spend across these efforts, the organization uses Invoca’s AI. With Invoca, Banner Health can see how many appointment calls each channel drives and track its true ROI. This allows it to double down on what’s working and cut spend on underperforming campaigns. As a result, they decreased patient acquisition costs by 74%.
To improve personalization, Banner Health also divides its audience into segments, including: loyal patients, patients who visit intermittently, and new patients. They provide each segment with customized website journeys — for example, new patients would receive “welcome” messaging. They also use segmentation to inform their bidding strategy — for instance, they can increase bids on new patients to prioritize acquisition and reduce bids on loyal patients who are likely to come back to them anyway.
Invoca has helped Banner Health build higher-performing segments by providing rich first-party data from callers. It has also allowed them to track the appointment calls their segmentation strategy has driven.
“Invoca has been critical for boosting the performance of our different audience segments. It has helped us understand what a loyal vs. a non-loyal patient’s experience looks like all the way through the funnel. From there, it has allowed us to improve the experience for each segment and build lasting loyalty,” said Chris Pace, chief digital marketing officer at Banner Health.
Read the full Banner Health case study here
3. A Leading Automotive Retailer Uses AI to Personalize Ads Based on Vehicle Interest
This leading automotive retailer’s mission is to provide a peerless car-buying experience. Therefore, it’s critical for the company to understand each customer’s needs and create a unified omnichannel experience for them. To accomplish this, it combined Invoca conversation analytics data with data from its digital channels to get a 360-degree view of every customer.
With Invoca, the auto retailer sends buyers personalized marketing campaigns touting the features they mentioned over the phone. It also gives its sales agents access to those insights, so they can tailor the conversation to win the sale. This creates a seamless omnichannel experience that makes every customer feel acknowledged and valued.
“The car buyer journey is different for everyone — some people want safety features and others want performance. Invoca has helped us tap into phone conversations so we can understand each buyer’s unique needs. As a result, we can deliver a truly peerless car-buying experience,” said the executive vice president of the leading auto retailer.
Additional Reading
Want to learn more about how Invoca can help you improve customer profiles and ad targeting? Check out these resources:
- How to Use First-Party Caller Data to Improve Audience Targeting Without Cookies
- How to Optimize Marketing Spend with First-Party Data from Phone Calls
- How to Calculate Your Return on Ad Spend (ROAS) — and Improve It
