Imagine a customer walks into your store, browses through products, and leaves without making a purchase. There’s no tracking to remind them about the products.
But, in the online space, you have retargeting.
Retargeting is about tapping into the psychology of potential customers, understanding their needs, and offering personalized and timely solutions.
Retargeting is more than just bombarding users with repetitive ads. It is a sophisticated art of re-engaging potential customers who have shown interest in your products or services but are yet to take that final leap. Marketers looking to widen their leads can use retargeting ads, offering a 1046% increase in branded search.
Plenty of retargeting techniques are designed to be more than just tools. They are a means to connect with your audience, build trust, and, ultimately, a path to conversion.
Let’s unravel four advanced remarketing techniques that help your brand engage with your digital audience.
First, let us understand how retargeting works.
How Retargeting Works?
Retargeting in digital marketing makes way for a subtle yet impactful reminder, a nudge to consumers who have already expressed an interest in your offerings.
The core lies in marketing reporting that creates metrics with clicks. A marketing report effortlessly shows data regarding individuals who have interacted with your brand at any point during the sales funnel (from awareness to purchase). It requires reconnecting with those individuals to guide them toward making a decision.
But how does this seemingly simple idea transform into a successful marketing strategy?
Let’s break it down.
It begins with a potential customer visiting your website, browsing through products or services, and leaving without further engagement, laying the groundwork for future retargeting efforts.
Tracking and Data Collection
The next step is to track these visitors and collect data. It is typically done through cookies or pixels placed on your website.
With JotURL, the conversion tracker can gather valuable information about visitors’ behavior, preferences, and engagement levels over a single dashboard.
You can then use this tracker for multi-touch attribution from sales, clicks, installations, and more. With actionable insights at your disposal, you’ll be able to take the next step toward retargeting.
Segmentation and Analysis
The collected data is segmented where potential customers are categorized based on their actions, interests, and level of engagement. For instance, someone who added a product to the cart but still needs to complete the purchase would be in a different segment than someone who merely viewed a product page.
Create tailored retargeting campaigns by using segmented data. These campaigns are designed to display personalized ads to segmented audiences across various digital platforms like social media, search engines, or partner websites.
Engagement and Conversion
Lastly, the goal is to re-engage these potential customers with relevant and compelling content that resonates with their previous interactions. Marketers go beyond serving a targeted reminder by presenting these products in a way that aligns with their interests and needs. This enhances the likelihood of conversion.
Let’s consider a case of B2C eCommerce –
A shopper browses summer apparel on an online store but leaves without making a purchase. Here, retargeting can be leveraged to exhibit personalized ads for the apparel they viewed. This audience segment can be retargeted with ads on social media, Google ads, and more. They can be intimated about discounts and special privileges like international priority shipping if it’s an overseas shopper. Such offers will nudge the shopper into revisiting the site and completing their purchase.
#1. Dynamic Creative Optimization (DCO)
Dynamic Creative Optimization (DCO) is a retargeting technique that dynamically alters ad content based on real-time data about the user.
Source: Dynamic Creates with Different CTAs
It’s about creating ads that are personalized to the nth degree. This means the content of the ad changes based on who the viewer is.
Two key factors here:
- Data Utilization: DCO utilizes data like browsing history, purchase behavior, and even real-time actions on a site.
- Ad Adaptation: Based on this data, the ad’s creative elements (images, messaging, offers) automatically adjust to suit each user.
For example, LinkedIn’s Dynamic Ads leverage DCO by leveraging:
- Personalization at Scale: LinkedIn Dynamic Ads automatically personalize ad content using profile data from LinkedIn members, such as their photo, company name, or job title.
- Targeted Messaging: This allows marketers to craft highly personalized messaging speaking directly to each user’s professional interests and status, making the ads more relevant and engaging.
Key steps to implement DCO
Step 1: Design Flexible Creative Templates
Design ad templates that are flexible for content changes. This includes text, images, CTAs, and other elements.
Step 2: Integrate with Cross-Channel Strategies
Ensure your DCO strategy aligns with your marketing strategy across channels. Message consistency is necessary regardless of where the customer sees your ad (social media, email, or display networks).
Step 3: Leverage Real-Time Data
Use real-time data triggers like location, time of day, or specific actions taken on your website to customize your ad content further.
Also, you’ll monitor these key metrics:
- Click-Through Rate (CTR): Analyze which creative variations yield higher CTRs and adjust your strategy accordingly.
- Conversion Rate: Identify ad variations leading to higher conversions and focus on similar content or offers in your campaigns.
- Engagement Rate: Use this data to understand which creative elements resonate best with your audience.
- Return on Ad Spend (ROAS): Calculate ROAS to assess the overall profitability of your DCO campaigns.
- Frequency: Monitor frequency to avoid overwhelming your audience and to keep your campaigns fresh.
- Quality Score (For PPC Campaigns): Improve ad relevance and landing page quality to increase your Quality Score, which can lead to lower costs and better ad positioning.
Step 4: Optimize for Conversion
Once analyzed, use these metrics to create a compelling call-to-action (CTA) that is aligned with the content to boost conversion rates
#2. Sequential Retargeting
Sequential Retargeting is a retargeting technique that shows a series of ads to potential customers in a specific order based on their previous interactions with your brand.
Source: Sequential retargeting of ads starting from the first touch.
This technique is about setting up a narrative that guides users through a journey that progressively builds interest and leads them closer to conversion.
Three key aspects:
- User Interaction Tracking: It needs to track how users interact with your site or initial ads.
- Staged Ad Delivery: Based on this interaction, you’ll create a sequence of ads displayed over time, each with a different message or call to action.
- Progressive Engagement: The idea is to move the user from awareness to consideration and then to decision-making, using ads tailored to each stage.
Suppose a user visits your B2B product page and explores its features. So, the first ad could show them more about the product. The next ad might highlight new or useful features that the product boasts.
Finally, you can target a special discount code or a limited-time offer that motivates decision-making.
How to get started with Sequential Retargeting
For starters, the following five steps can help kickstart your retargeting journey.
- Map the Customer Journey: Understand the different stages in your customer’s journey and what type of messaging appeals to them at each stage.
- Content Variation: Create diverse content for different stages – introductory ads, feature-specific ads, and finally, conversion-focused ads.
- Timed Sequences: For effective spacing of sequential ads, consider the typical decision-making timeline of your audience and space the ads to align with this cycle. Allow a few days to a week between each ad, ensuring users have time to process the information without feeling overwhelmed.
- Track User Response: Monitor how users interact with each ad. To track user response in sequential retargeting, set up analytics to monitor interactions with each ad, such as click-through rates, time spent on the ad, and conversion actions. This data helps understand user engagement at each stage to optimize future ad content and sequencing based on these insights. This data is crucial for optimizing the sequence and content of future ads.
- Personalization: Tailor the sequential ads based on user behavior. The more personalized the sequence, the more effective it will likely be.
Key Metrics to Monitor
Engagement Rate per Ad: This metric represents how users interact with each ad in the sequence. A positive engagement rate would mean it is a good idea to push a purchase CTA ad with offers/discounts.
Drop-off Rate: When did the user stop engaging with the sequential ad tracking? A consistent drop-off at each sequence may signify the prospect of losing interest in your product.
Conversion Rate by Stage: Analyze which ads in the sequence drive conversions if you adopt the DCO method at each sequence.
#3. Cross-Device Retargeting
Cross-device retargeting addresses the modern reality where users switch between multiple devices daily. This technique involves tracking and retargeting the same user across different devices, providing a consistent and cohesive marketing message.
Source: Reaching to users through different devices they use
For instance, Amazon excels in cross-device retargeting. Whether you’re browsing on a phone, tablet, or desktop, Amazon’s ads for products you’ve viewed or related items consistently appear across these devices, keeping the products top of mind.
How does it work?
Unified User Profile: Build a unified profile for each user by tracking interactions across various devices like smartphones, tablets, laptops, etc.
Synchronized Retargeting: Display retargeted ads to reflect the user’s most recent interactions with your brand, regardless of their viewing device.
How do we implement this technique?
Utilize Unified ID Solutions
Implement unified ID technologies to identify users across devices without relying solely on cookies. Using JotURL branded links, you can create tailored links to create a compelling URL that communicates something about your link. This can help drive higher conversion rates by better understanding user behavior across different devices.
Leverage Machine Learning for Predictive Analysis
Use machine learning algorithms to analyze cross-device usage patterns and predict the most effective times and devices for ad delivery. With this, your ads are served when and where they’re most likely effective in taking an action.
Implement Frequency Capping
Limit the times your ad is shown to the same user across different devices in a given period using your ad platform’s settings. This approach helps prevent ad fatigue and maintains a positive brand perception.
Key Metrics to Monitor:
- Device-Specific Engagement: Use analytics platforms like Google Analytics or Adobe Analytics to segment data by device type. Analyze metrics like click-through rates, time on site, and interaction rates on ads for each device category (mobile, desktop, tablet).
- Conversion Path Tracking: Leverage Cross-device tracking features in your analytics tools or employ Unified ID solutions. Track the user journey across devices from the first ad interaction to the final conversion that needs looking at multi-touch attribution models.
- Frequency and Reach: Ad platforms (like Google Ads or Facebook Ads Manager) typically offer frequency and reach reporting. Set up your ad campaigns to tag users and monitor how often your ads are served across devices. Use this data to adjust frequency caps and campaign targeting.
#4. Predictive Retargeting
Predictive Retargeting takes personalization a step further by using machine learning and artificial intelligence to predict future customer behavior based on past actions. This technique responds to past interactions and anticipates future needs and interests of users.
A B2B software company specializing in project management tools leverages predictive retargeting to enhance its marketing efforts. They analyze data from their website, including which businesses are looking at specific features, how long they spend on informational pages, and past purchasing patterns.
Based on such information, it yields the following:
- Predictive Analysis: The AI system identifies patterns, suggesting that businesses browsing advanced features are likely scaling rapidly and might soon need more robust solutions.
- Targeted Campaigns: Predictive data helps create tailored ads focusing on scalability and advanced features, targeting these businesses before they actively search for new solutions.
How does it work?
- Data Analysis: AI algorithms analyze large sets of user data, including past browsing and purchasing behaviors.
- Behavior Prediction: It can predict future actions, identifying users likely to convert or show interest in specific products or services.
- Targeted Ad Delivery: Based on this prediction, you can create and deliver ads to effectively address users’ future needs or interests.
How to Use This Technique?
Explore the AI-driven retargeting technique by following the below actionable tips:
Use Advanced Analytics Tools
Choose analytics tools that can handle large datasets and offer detailed insights. Tools like Google Analytics 360, Adobe Analytics, or specialized platforms like JotURL can provide in-depth tracking capabilities for better decision-making.
These tools require integrating data from different sources (Social media, paid ads, SEO, etc.) with your existing CRM and marketing automation platforms for a unified data ecosystem.
Tailor Creative to Segments
The analysis from such tools can help create ad content that directly resonates with each segment’s predicted needs and interests. For instance, your analytics suggest that a customer segment prioritizes efficiency in its operations. Then, the ad content should focus on how your product or service enhances operational workflows, reduces time on tasks, or integrates seamlessly with existing systems.
Refine Customer Segments Continuously
Schedule frequent reviews of customer data to keep segments up-to-date with changing behaviors and market trends. Ideally, create feedback mechanisms where sales and customer service insights are used to refine segmentation models. Accordingly, quickly tweak your marketing strategies in response to new data insights.
Implementing Predictive Retargeting
Employ AI tools that can predict future customer behavior based on past interactions. Platforms like IBM Watson, Salesforce Einstein, or custom-built AI solutions can be powerful assets. They provide predictive modeling that helps develop models forecasting future buying behaviors, potential upsell opportunities or churn risks.
Note: Always consider the ethical implications and privacy concerns when using predictive data to remain compliant with data protection regulations like GDPR or CCPA.
Key Metrics to Monitor
Predictive Accuracy: Evaluate how accurately the predictive model identifies potential converters.
Conversion Rates Post-Prediction: Measure the conversion rates of users targeted based on predictive analysis.
Customer Lifetime Value (CLV): Track the CLV of customers acquired through predictive retargeting to assess long-term value.
The future of digital marketing is not just about reaching audiences but engaging with them in a more meaningful, personalized way. By leveraging these advanced strategies, marketers can create campaigns that are targeted and deeply resonant with their audience’s current and future needs.
The key takeaway for marketers is to embrace these advanced retargeting techniques, not as mere tools but as integral components of a comprehensive digital marketing strategy.
Remember, the goal is to create a marketing ecosystem where each interaction is an opportunity to deepen the relationship with your audience. By doing so, you’re not just capturing their attention; you’re earning their trust and loyalty.
Guest Author –
Virginia Andrus is an independent Digital Marketing Consultant with 6+ years of marketing experience. Virginia is a chef by heart. In her free time, she is either writing marketing copies for brands and agencies or experimenting with new recipes at her home. Connect with her on Twitter: @andrus_virginia.