How To Create Your Own Lookalike Audiences?

How To Create Your Own Lookalike Audiences?

Lookalike audiences have become a powerful tool for expanding reach and finding new potential customers in the age of digital marketing. Obviously if you know who your customers are, people who share their most common characteristics are also likely to be interested in your product or service.

But although platforms like Facebook offer built-in lookalike audience features, these automated solutions don't always hit the mark. Anyone who follows the page of a particular football club, and is then told that “a page they should like” is the one belonging to their deadly rivals, which they would never be seen dead looking at, will readily see the limitations of the Facebook lookalike algorithms. 

Creating your own lookalike audiences can generate more accurate targeting and better campaign performance. This article will guide you through the process of creating your own lookalike audiences which will help you supplement and improve upon platform-generated options.

Understanding Lookalike Audiences

In order to develop them effectively it's important to understand exactly what lookalike audiences are.

Lookalike audiences are groups of people who share similar characteristics, behaviours or interests with your existing customers or high-value prospects. This can be assessed in a number of ways, either manually or through machine learning tools.

The idea is that these similarities make those individuals more likely to be interested in your products or services. Although this is only the case if you have identified the right characteristics and catered to them successfully, if you can create your own lookalike audiences these are skills you will be able to develop, with the assistance of a digital marketing agency. 

Why Create Your Own Lookalike Audiences?

a. You have more control over the audience characteristics

b. Your audiences have greater alignment with your specific business goals

c. You can incorporate unique insights about your customers

d. You can gain higher conversion rates and ROI

e. You are less reliant on the black-box algorithms of advertising platforms

f. Steps to Creating Your Own Lookalike Audiences

g. Define Your Seed Audience

The first step in creating a lookalike audience is to define the group of existing customers or prospects you want to model your new audience after. This is known as your seed audience. Best practices here are:

a. Start with your best customers (e.g., repeat buyers, high lifetime value customers)

b. Focus on customers who have made recent purchases

c. Include customers who have engaged deeply with your brand (e.g., email subscribers, app users)

d. Ensure your seed audience is large enough to be statistically significant (aim for at least 1,000 individuals)

A. Gather Comprehensive Data on Your Seed Audience

To create an accurate lookalike audience, you need detailed information about your seed audience which is relevant to your sales strategy. These are the data points to collect:

a. Demographic information (age, gender, location, income level)

b. Psychographic data (interests, values, lifestyle)

c. Behavioural data (purchasing habits, online behaviour)

d. Professional information (job title, industry, company size)

B. Analyse Your Seed Audience Data

Patterns and commonalities within your seed audience can be treated as sales drivers. The most common analysis techniques are:

a. Use data visualisation tools to spot trends

b. Conduct cluster analysis to identify distinct segments within your audience

c. Calculate averages and ranges for key metrics

d. Identify the most common characteristics and behaviours

C. Define Your Lookalike Criteria

Based on your analysis, determine the key characteristics which define your ideal customer. The factors you need to take into account are:

a. Which traits are most common amongst your best customers?

b. Which behaviours correlate strongly with high customer value?

c. Are there any surprising insights which challenge your assumptions?

D. Use Data Enrichment Services

To expand your understanding of your seed audience and create more accurate lookalikes, consider using data enrichment services.Some popular data enrichment tools are:

a. Clearbit

b. FullContact

c. ZoomInfo

d. Datanyze

These services can provide additional insights about your customers, such as company information, social media profiles and technology usage.

E. Leverage Predictive Analytics

Use predictive analytics tools to identify the characteristics most likely to indicate a high-value customer. Steps:

a. Build a predictive model using your seed audience data

b. Identify the variables most predictive of customer value

c. Use these insights to refine your lookalike criteria

1. Create Detailed Personas

Develop detailed customer personas based on your analysis and enriched data. Elements to include are:

a. Demographic details

b. Professional information

c. Interests and hobbies

d. Pain points and challenges

e. Preferred communication channels

f. Typical buying journey

2. Use Lookalike Modeling Tools

While not relying entirely on platform-generated lookalikes, you can still use lookalike modelling tools to refine your audience. Options here are:

a. Customer Data Platforms (CDPs) with lookalike modelling features

b. Machine learning platforms which allow custom audience modelling

c. Data management platforms (DMPs) with audience expansion capabilities

3. Test and Refine Your Lookalike Audiences

Once you've created your lookalike audience, it's crucial to test and refine it. The usual testing methods are:

a. Run small-scale advertising campaigns to different segments of your lookalike audience

b. Use A/B testing to compare performance against platform-generated lookalikes

c. Monitor key metrics like click-through rates, conversion rates and customer lifetime value

4. Use Cross-Channel Verification

To ensure the accuracy of your lookalike audience, verify its performance across multiple channels. The channels to consider include:

a. Social media advertising

b. Display advertising

c. Email marketing

d. Content marketing

5. Use Intent Data

You should incorporate intent data to identify individuals who are actively researching products or services similar to yours. Sources of intent data are:

a. B2B intent data providers (e.g., Bombora, TechTarget)

b. Website visitor identification tools

c. Search data from your own website

6. Leverage Technographic Data

B2B companies or tech-related products should also use technographic data to refine their lookalike audiences. Technographic data points to use are:

a. Technology stacks used by companies

b. Software preferences

c. Hardware usage

d. Technology adoption patterns

7. Segment

Rather than creating one large lookalike audience, segment your lookalikes based on specific criteria. Segmentation criteria include:

a. Product interest

b. Industry

c. Company size

d. Geographical region

e. Stage in the buying journey

8. Use Exclusion Lists

To improve the accuracy of your lookalike audience, create exclusion lists to remove individuals or companies which don't fit your ideal customer profile. Potential exclusions are:

a. Competitors

b. Current customers (if you're focusing on acquisition)

c. Companies in irrelevant industries

d. Individuals with mismatched job titles

9. Incorporate Customer Feedback

Use feedback from your sales and customer service teams to refine your lookalike criteria. Areas to explore are:

a. Common objections during the sales process

b. Frequently asked questions from prospects

c. Characteristics of customers who have the highest satisfaction rates

10. Utilise Social Media Insights

You should leverage the wealth of data available from social media platforms to enhance your lookalike audience. This is how you do it:

a. Analyse the social media profiles of your seed audience

b. Look for common interests, followed accounts and engagement patterns

c. Use social listening tools to identify relevant conversations and trends

11. Implement Dynamic Lookalike Audiences

Create a system for continuously updating and refining your lookalike audiences based on new data and performance insights. This is the process:

a. Set up regular data refreshes from your CRM and other data sources

b. Implement automated performance tracking and audience adjustment

c. Regularly review and update your lookalike criteria based on changing business goals and market conditions

12. Use Contextual Targeting to Supplement Lookalikes

Combine your lookalike audiences with contextual targeting to improve relevance and performance. Contextual targeting factors to include are:

a. Website content

b. Time of day

c. Current events

d. Seasonal trends

13. Implement Offline Data Integration

Businesses with significant offline operations should integrate offline data to create more comprehensive lookalike audiences. The best offline data sources are:

a. In-store purchase data

b. Phone call logs

c. Direct mail responses

d. Event attendance records

14. Observe Ethical and Privacy Implications

As you create and use lookalike audiences it's crucial to consider the ethical implications of using this data and comply with data privacy regulations. Best practices here are:

a. Ensure all data collection and usage complies with relevant laws (e.g., GDPR, CCPA)

b. Be transparent with your audience about how their data is being used

c. Provide clear opt-out mechanisms for data collection and targeting

d. Regularly audit your data practices to ensure ongoing compliance

Conclusion

Creating your own lookalike audiences offers a powerful way to enhance your digital marketing efforts and find new potential customers who are likely to be interested in your products or services. By taking control of the process you can create more accurate, nuanced audiences which align closely with your business goals and customer insights.

Creating effective lookalike audiences is an ongoing process. You’ll need to continuously test, refine, and update your audiences based on performance data and new insights. 

Nevertheless, by combining your own lookalike audiences with platform-generated options and other targeting strategies, you can create a comprehensive, data-driven approach to audience targeting which drives better results and higher ROI for your marketing campaigns. Maintain ethical data practices and thus build trust with your audience, creating a foundation for long-term marketing success.