Introduction
This tutorial is designed for medium to advanced advertisers looking to leverage data-as-a-service (DaaS) to generate leads and sales. The objective is to guide you through setting up a DaaS model using AudienceLab to target specific audiences, deliver high-quality data to clients, and minimize fulfillment work. By the end of this tutorial, you will understand how to position yourself as a DaaS provider, structure your offerings, and implement strategies that convert data into revenue.
Step 1: Understanding the DaaS Model and Its Benefits
What is Data-as-a-Service (DaaS)? Data-as-a-Service is a business model where you provide clients with targeted data that they can use for their marketing and sales efforts. Unlike traditional services where you manage the entire marketing campaign, DaaS focuses on delivering high-quality, actionable data that the client can use independently. This model is ideal for those who want to run an agency without the heavy lifting of full-scale service fulfillment.
Key Benefits of DaaS:
- Low Fulfillment Work: You provide data, not full-service marketing, which reduces the need for ongoing client management.
- Scalable Revenue: Once you set up your data pipeline, you can scale easily by onboarding more clients.
- Specialized Expertise: Position yourself as a specialist in data rather than a generalist agency, which can make you indispensable to clients.
Case Study: Emmett’s Transition to DaaS Emmett originally ran a full-service agency, managing everything from creative to ad reporting. However, by transitioning to a DaaS model, he eliminated the need for constant client meetings and detailed fulfillment work. Instead, he focused on providing highly targeted data that clients could use to improve their own marketing efforts.
Step 2: Identifying Your Target Market with AudienceLab
AudienceLab Overview: AudienceLab is a powerful platform that allows you to generate targeted audiences based on specific behaviors, demographics, and interests. Whether your clients are targeting local consumers or specific industries, AudienceLab provides the data needed to reach those audiences effectively.
How to Use AudienceLab:
- Sign in to AudienceLab: Begin by logging into your AudienceLab account.
- Set Your Parameters: Define your target audience by specifying key criteria such as location, interests, and behaviors. For example, if your client is a roofing company, you would target homeowners recently searching for roofing services.
- Generate and Download Your List: Once your criteria are set, AudienceLab generates a list of prospects that match your target audience. You can review and download this list for use in your client’s marketing campaigns.
Case Study Example: Roofing Client Emmett worked with a roofing company that did not want to run traditional ads. Instead, he used AudienceLab to identify households actively searching for roofing services, then provided this targeted list to the client, who was able to achieve a 10-20% conversion rate from door-knocking efforts based on this data.
Step 3: Setting Up and Testing Data in Client Ad Accounts
Why Testing is Crucial: Testing your data within the client’s ad account is critical to proving its effectiveness. Without proper testing, clients may question the value of the data, especially if their cost-per-lead initially increases.
How to Set Up a Campaign Using AudienceLab Data:
- Upload the Data: Start by uploading the AudienceLab-generated list into the client’s Facebook Business Manager.
- Create a Custom Audience: Use the data to create a custom audience in Facebook, which can be used to run targeted ad campaigns.
- Implement Dynamic Testing: To ensure the best results, create a 1-4% lookalike audience and run a dynamic creative test. This approach “tricks” Facebook’s algorithm into spending on your smaller, highly-targeted audience by combining it with broader lookalikes.
Case Study: Emmett’s Success with Dynamic Testing Emmett found that by running dynamic tests with both custom and lookalike audiences, he was able to significantly improve his clients’ conversion rates. Although the cost per lead was slightly higher, the quality of leads improved, leading to a lower overall cost per acquisition (CPA) for his clients.
Step 4: Automating Data Delivery with Webhooks
The Power of Webhooks: To streamline data delivery and bypass manual upload restrictions on platforms like Beehive, you can set up a webhook. This allows you to automatically transfer engaged prospects from platforms like Instantly to Beehive, ensuring a seamless and compliant data flow.
How Nic Set Up Webhooks to Bypass Beehive Restrictions: Normally, Beehive imposes limits on manually uploaded lists, particularly when the list size exceeds 10,000 contacts. Nic was able to bypass these restrictions by setting up a webhook using ActivePieces. This webhook allowed him to automatically sync smaller, regular batches of data from Instantly to Beehive without triggering any upload limits.
Step-by-Step Webhook Setup:
- Create a New Webhook in ActivePieces: Set up a new webhook that triggers whenever a new contact is added to your Instantly list.
- Configure the Action: Link this webhook to Beehive, where it will automatically subscribe new contacts to your newsletter or client’s database.
- Test and Activate: Run tests to ensure the webhook is functioning correctly, then activate it for continuous data syncing.
This method not only ensures compliance with platform rules but also keeps the data flow efficient and hands-off.
Step 5: Monetizing Your Data Services
Data Monetization Strategies:
- Audience Syncing: Charge clients a monthly fee to sync targeted audiences directly to their ad accounts. For instance, Emmett charges $1,500 to $2,500 per month per audience.
- Canvassing: Provide clients with highly targeted lists for door-knocking or direct mail campaigns. This method is especially effective for local businesses looking to maximize outreach without digital advertising.
- Custom Models: Offer clients custom-built audiences based on specific keywords or behaviors. By using AudienceLab’s AI to sift through billions of URLs, you can deliver highly accurate and relevant audiences.
Case Study: Roofing Company Canvassing Emmett used canvassing to help a roofing company target households in specific zip codes actively searching for roofing services. By providing this data, the company achieved a high conversion rate and significant ROI, generating $30,000 in revenue from a $2,500 investment in the list.
Step 6: Analyzing and Optimizing Your Campaigns
Why Continuous Analysis is Important: After setting up your DaaS model, it’s essential to regularly analyze campaign performance to ensure ongoing success. This includes monitoring key metrics such as open rates, conversion rates, and overall ROI.
Metrics to Focus On:
- Open and Click Rates: Ensure that your email campaigns are engaging enough to drive conversions.
- Cost Per Acquisition (CPA): Track how the data you provide is impacting the client’s overall cost to acquire a customer.
- Client Retention: Regularly check in with clients to ensure they are satisfied with the data and are seeing a positive return on investment.
Example: Client Feedback Loop Emmett uses GoHighLevel (GHL) to send automated reminders to clients, updating them on the number of leads or data lists they’ve received. This keeps the service top-of-mind and reinforces the value provided, leading to higher client retention rates.
Step 7: Finding Clients and Scaling Your DaaS Business
Targeting the Right Clients: To scale your DaaS business, focus on clients who already have some level of marketing infrastructure in place, such as those running ads or maintaining a CRM. These clients are more likely to see immediate value in the data you provide.
Strategies to Find Clients:
- Run Targeted Ads: Use SIC codes to identify and target specific industries that would benefit from your data services.
- Leverage B2B Networks: Identify companies using technologies that align with your offerings, then reach out with a targeted proposal.
- Client Vetting: Focus on clients who already have a system in place to handle the leads or data you provide, ensuring they can maximize the value of your service.
Case Study: Emmett’s B2B Approach Emmett runs targeted ads to agencies using specific SIC codes, offering a direct and clear value proposition. By targeting businesses that are already spending on marketing, he ensures that the data provided leads to immediate results, increasing client satisfaction and retention.
Conclusion
Transitioning to a Data-as-a-Service model can significantly reduce the workload while providing substantial value to your clients. By leveraging tools like AudienceLab, implementing automated data delivery through webhooks, and focusing on high-quality audience targeting, you can create a scalable, profitable business model. Whether you’re looking to expand your agency or shift to a more hands-off approach, the strategies outlined in this tutorial will help you achieve your goals
