What Are Unique Methods for Audience Segmentation Using Marketing Technology?
Martech Interviews
What Are Unique Methods for Audience Segmentation Using Marketing Technology?
Delving into the art of audience segmentation, we've gathered insights from eleven marketing mavens, including directors and CMOs, on their unique methods leveraging the latest in marketing technology. From implementing cross-platform identity mapping to harnessing CRM and AI for niche segmentation, discover the innovative strategies these experts are using to tailor their marketing efforts.
- Implement Cross-Platform Identity Mapping
- Leverage AI-Driven Predictive Analytics
- Segment by Ice-Cream Flavor Preferences
- Utilize Geodemographic Segmentation
- Explore Deep Psychographic Segmentation
- Segment With Digital Engagement Metrics
- Analyze Behavior With Heatmaps
- Categorize Using Story-Like Chatbots
- Hyper-Target With Facebook User Data
- Segment Using Machine-Learning Algorithms
- Harness CRM and AI for Niche Segmentation
Implement Cross-Platform Identity Mapping
We've implemented a cross-platform user identity mapping technique that segments audiences by tracking their interactions across various digital touchpoints. By developing a unified customer view, we can deliver a seamless and personalized marketing experience on any platform. This method is particularly useful for omnichannel marketing campaigns, as it ensures that our messaging is consistent and relevant across all platforms, enhancing the overall effectiveness of the campaign.
Moreover, this approach allows us to track the customer journey more accurately, identifying key touchpoints and opportunities for engagement. It enhances our ability to personalize content and improves our measurement and analytics capabilities, giving us deeper insights into campaign performance and customer behavior.
Leverage AI-Driven Predictive Analytics
At Write Right, we use AI-driven predictive analytics to segment our audience. By integrating AI tools with our CRM, we analyze user behavior, engagement patterns, and historical data to predict future actions and preferences.
For example, we track metrics like content interaction, email open rates, and website navigation paths. The AI then groups these data points to find audience segments with similar behaviors and interests. We look at psychographics and behavioral tendencies, not just demographics.
A particularly effective approach was creating dynamic content streams. Based on the AI's predictions, we tailor our content delivery in real time. For instance, academic writing clients receive tailored advice and case studies, while corporate clients get insights on business writing trends.
This method has greatly improved our targeting accuracy, resulting in a 25% increase in engagement and a 15% boost in conversion rates. By understanding and predicting our audience's needs more precisely, we deliver personalized experiences that resonate deeply, driving higher satisfaction and loyalty.
Segment by Ice-Cream Flavor Preferences
Ever tried segmenting your audience by their favorite ice-cream flavors? Yep, really! We sent out a fun survey and discovered sweet-toothed trends that aligned perfectly with our campaign goals. It added a playful twist to our strategy, and voilà, our engagement skyrocketed! What's more, it's led to our highest conversion rates yet. Try it out—your audience might savor it as much as we did!
Utilize Geodemographic Segmentation
As a global business, one of the most important aspects of segmentation is geographic. However, it's not as simple as just dividing our audience by region, as that can be quite a crude way of segmenting. Instead, we use geodemographics to segment by both location and demographics, allowing us to target our message based on region and customer characteristics.
For example, we send out communications in multiple languages, but we can't assume language based on location, and there are also cultural nuances to language depending on the specific area. Using geodemographic segmentation allows us to adjust our messaging and tone depending on location, culture, and the customers' preferred language.
Explore Deep Psychographic Segmentation
Our marketing agency has used psychographic segmentation to delve into the psychological aspects of various audiences for different clients. This includes both B2B and consumer behavior, such as values, attitudes, interests, and lifestyles. While this method of market research requires quite a bit of in-depth data collection, including polls, surveys, and social media monitoring tools, it is incredibly valuable when writing copy and developing ads to appeal to different audiences.
For example, we can look at personality traits, such as whether customers are introverted or extroverted, risk-averse or risk-takers. We can look at their lifestyles, such as how customers prefer to spend their leisure time, their hobbies, even what books they read or movies they watch. We also look at what customers value most, such as sustainability, innovation, or tradition, or simply price and perceived value of a product.
By understanding these deeper psychological factors, we can create campaigns that align with the intrinsic motivations of our clients’ audiences, fostering stronger emotional connections, and—most importantly—increasing conversion rates and making more sales.
Segment With Digital Engagement Metrics
Collect data on interactions such as email open rates, click-through rates, website visits, and social media engagement to segment your email marketing audience using prior digital engagement metrics. Utilize this data to categorize your audience based on their activity levels and preferences.
You can start with data collection by gathering metrics from emails, websites, and social media platforms. From there, once you know the data available, focus on the most important engagement indicators, like open rates, clicks, page views, and social shares. Then, you can use your marketing automation tool to build lists and create segments such as highly engaged users, occasional clickers, and inactive subscribers.
Once you have this critical data, you can leverage it to build personalized campaigns by targeting email content to each segment. For instance, send exclusive offers to highly engaged users and re-engagement emails to inactive subscribers. This will help you deliver more relevant content based on past behavior and increase your email open and click rates by sending highly tailored messages to a segmented audience.
Analyze Behavior With Heatmaps
I’ve used behavioral segmentation through heatmaps and session recordings. Watching where people click, hover, and scroll on our website gave us a goldmine of data on user behavior. It’s like digital people-watching but with less awkwardness. We found that grouping users based on their on-site actions, such as repeated clicks on certain elements or rage-clicking when things don't work, led to more targeted and effective campaigns. I think it’s a brilliant way to really understand what gets under your audience's skin.
Categorize Using Story-Like Chatbots
We segment our audience by creating categories through a chatbot. With chatbots, we can directly ask our users questions, engage with them, and provide them with tailored content that meets their needs. This approach helps solve some of their problems and supports them on their journey.
The more we learn about our users, the better we can identify the content they're genuinely interested in, enriching their lives. Chatbots let us interact with our audience in a story-like way, making them feel like the story is crafted just for them.
When people start chatting with our chatbot, the first question is, "Can we chat with you today?" This sets up an opt-in conversation. Once we get a positive response, we might ask, "Would you like to see case studies, business use cases, or hands-on tactics?" Based on their place in the buyer's journey and their background, we can better understand what they want to learn and engage with them more effectively.
Hyper-Target With Facebook User Data
I've personally tried segmenting an audience using Facebook user data. Personalization has become an essential trend in marketing over the past few years, and technology has made it increasingly accessible for marketers using platforms they're already familiar with.
We've become quite adept at using advertising platforms like Facebook, which allows for hyper-targeting our customers. Facebook Ads Manager provides incredibly detailed options for demographic and psychographic audience targeting—from interests and behaviors to job titles and locations. We take it a step further by asking the audience direct questions to better understand who they are. This is particularly effective using website chatbots and click-to-Messenger ads that lead into automated messaging sales funnels.
The significance of utilizing our contact segmentation tools cannot be overstated in modern marketing, as higher engagement rates often lead to greater organic reach and improved conversion rates.
Segment Using Machine-Learning Algorithms
A unique method we’ve employed to segment our audience using marketing technology is through the use of advanced machine-learning algorithms to analyze behavioral data and create dynamic customer segments. Instead of relying solely on traditional demographics, we leverage data from various touchpoints, such as website interactions, social media engagement, purchase history, and even customer service interactions. By feeding this data into machine-learning models, we can identify patterns and predict future behaviors, allowing us to segment our audience based on their predicted needs and preferences.
For example, we implemented a recommendation engine on our e-commerce platform that segments customers in real-time. This engine analyzes a customer’s browsing and purchasing behavior, then dynamically segments them into groups like “bargain hunters,” “loyal customers,” or “trend followers.” These segments receive tailored marketing messages and personalized offers. As a result, we saw a 25% increase in conversion rates and a 30% boost in customer retention, demonstrating the power of machine-learning-driven segmentation in enhancing marketing effectiveness and customer satisfaction.
Harness CRM and AI for Niche Segmentation
Through my expertise in data-driven marketing and digital transformation, I've discovered novel ways to segment audiences using marketing technology. One unique method employed at Businessmap involves harnessing advanced CRM systems integrated with AI algorithms for niche segmentation. This allows us to draw valuable insights, predict behavior, and create hyper-personalized campaigns.
Another approach is leveraging social media analytics on platforms such as Instagram and Facebook. These platforms provide demographic, psychographic, and behavioral data, which we categorize into micro-segments for targeted content delivery.
Lastly, we have used SEM tools to infer audience intent based on search patterns. This method helps us understand the customer journey and design effective engagement strategies. Capitalizing on these unique segmentation methods has led to optimized outreach and a significant enhancement in customer engagement.
