Whether you are an e-commerce brand offering subscriptions for apparel, nutrition, or similar products, an educational content business offering online classes, or a software platform or app with subscription services…
You probably leverage some form of try-before-you-buy or free trial sign-up model to attract new customers. And although it is a great customer acquisition strategy, this model often comes with significant challenges of acquiring low-quality sign-ups that don’t convert and end up churning before the trial period ends.
This is hurting your business. Acquiring low-quality sign-ups is not only wasting ad dollars but also putting a strain on your financial and operational resources during trial periods when supporting users who have no intention of converting.
So, in this article, we are talking about the challenges of acquiring low-value sign-ups and strategies you can implement to acquire high-quality signups that actually convert for long-term subscriptions, helping increase your customer LTV and lower acquisition costs.
Are you ready to make your try-before-you-buy or free trial sign-up model more effective?
Let’s dive in!
Observations, strategies, and recommendations made in this article are based on our findings working with some successful Angler AI partner businesses and brands that use the try-before-you-buy models across a spectrum of products and services -
Wantable (a personalized apparel subscription box) - Wantable offers customers a personal styling service for a small fee. After the session, customers can try on looks and return the items they don’t like, only paying for what they keep.
Online classes subscription - Given this popular service’s yearly subscription, they offer a 30-day money-back guarantee for any customers who are not satisfied with the content.
Personal finance & budgeting app subscription - A fast-growing service that offers a 30-day free trial for customers to try its full feature set before committing to a monthly fee.
Let’s first discuss what makes try-before-you-buy model great for both businesses and consumers.
Consumers love try-before-you-buy products for 2 big reasons -
No commitment or minimal financial commitment
In most instances customers really only need to enter their payment information, but don’t get charged at sign-up.
In other cases, like with Wantable, customers might have to pay a small initial fee, e.g., $20, for a personal styling service. However, there is no additional cost to try their products before committing to a subscription.
A chance to make sure they like it
Customers can use the product before making a decision, and don't risk getting stuck with products they don't like. They can cancel their subscription, return the item, or get a guaranteed refund.
These two reasons reduce the friction for a prospective customer to try a brand, potentially leading them to become a long-term customer.
Businesses also benefit from the free-trial model as this strategy helps them -
Attract High-volume, cheap top of funnel traffic
Given low or no financial commitment, it is an easy and cost-effective for businesses to acquire new customer signups and attract more prospects in the signup funnel.
This expanded volume of sign-ups and prospects leaves valuable breadcrumbs and clues about other audiences with their behavioral data.
Brands can use this data effectively to optimize for additional signups at low cost on ad platforms like Meta and Google.
Get payment method on file
The sign-up process typically requires customers to add their credit card or other payment information during a high-intent but low-risk part of the flow. Once a payment method is on file, it eliminates friction at the end of the trial or for repeat orders. This makes it easier for brands to convert more customers by reducing extra steps and decisions for buyers.
Brands acquire lots of data on what's working and what's not
The biggest advantage of this business model is that brands capture consumer preferences through pre-signup quiz responses and tracked activity during the trial period, as well as "loss" data from orders and customers who canceled subscriptions or made partial refunds.
Over time, brands have an opportunity to build valuable 0-party and 1st-party data on customers and prospects, their preferences, and their transaction information, which they can use to improve both their marketing and product.
The try-before-you-buy and free-trial model does not come with all benefits and no challenges. Businesses can also struggle optimizing this model due to the following challenges -
Wasted Spend & Product
When offering a free trial, brands naturally lower the bar for customers to sign up compared to a purchase. This means that there will be more lower intent consumers signing up to try the product or service, which may not be a good fit for many of them.
As a result, many of these customers will either never purchase or churn early, generating little or no revenue for the brand.
Low-quality signups also create serious financial challenges for brands because they spend their valuable marketing dollars acquiring these signups, which don’t lead to conversions for post-trial paid subscriptions.
Additionally, there may have been other costs incurred by brands to serve those customers' first orders, causing the brand to lose money on labor, shipping, and processing or restocking merchandise.
Difficulty in Optimizing Ad Spend
Walled garden ad platforms (closed systems that let you access user data only through their platform) like Meta, Google Ads, and TikTok need customer purchase events via a real-time pixel or server-side integration to improve conversion campaigns.
For brands offering free trials, there is a long period (at least days, often weeks) between ad impressions (when people see ads), site engagement (when they visit the website), and sign-up events to the eventual revenue event (when they finally pay).
Due to longer attribution periods, ad optimization algorithms struggle to determine which ad impressions and sign-ups lead to sales, resulting in high cost-per-purchase metrics and relatively low return on ad spend (ROAS).
Now that we understand both the benefits and challenges involved with these customer acquisition models, let’s discuss strategies that can help you make this model effective and help you win more quality sign-ups that lead to higher conversions post free-trial periods.
Collect & Verify Persistent Identifiers - When customers sign up for your product or service, make sure you collect persistent identifiers like email addresses or phone numbers and verify them. These data points can be used not only for CRM messaging when guiding customers through the trial process but also as a way of linking all their future activity to them and matching them to ad platform users.
Store Marketing Click & Pixel Identifiers - If you have a landing page that precedes your signup page, make sure you are sending your marketing click and pixel identifiers, like fbclid
, fbp
, gclid
, etc., to your database, analytics solution, or advanced C-API solution. These will need to be stitched to later customer activity, like signup, trial actions, and conversion, so that the original ad clicks and views get the necessary credit for the trial and conversion.
Engage & Nurture with Personalized Responses - If you have a pre-signup flow that collects quiz or survey answers, make sure to store this information in a Customer Data Platform (CDP), database, or e-commerce data layer. This data is valuable for segmenting users and engaging with them in a personalized way to nurture them along the journey towards successful conversions.
For example - The personal finance & budgeting app we mentioned above does this well by tracking all of this information using a combination of analytics solution and advanced Conversions-API (C-API). This enables it to properly attribute campaigns and optimize best performing channels.
Avoid Under-Attribution of Paid Social
With the longer consideration periods of free trials, it is important to consider multi-touch attribution models. Often, due to CRM and other campaigns engaging and retargeting customers who have already signed up which helps move customers along the trial funnel — last-touch models give undue credit to these other channels and under-attribute first-touch channels like paid social. Using proper data collection techniques as mentioned above allows later events to be enriched with first-touch identifiers and enables proper attribution to campaigns, giving you a holistic view of the customer journey for more informed decision-making when scaling campaigns.
For example - Previously Wantable tracked visitors on their site and attributed marketing sources by showing which last-touch source they came from. By using an advanced C-API solution with session stitching and data enrichment, they were able to better understand the impact of paid social channels and how they drove signups leading to conversions.
Use AI to predict the value of sign-ups.
With advancements in cutting-edge AI tech, it has now become easier than ever for brands to predict the real value of each sign-up to paint a clear picture of which sign-ups will eventually convert into paying customers.
Proper data collection, identification, enrichment, and attribution allow AI models to learn the common patterns of customers who not only sign up but also eventually convert.
The best AI models look at and learn from source channels, users' onsite activity, their quiz responses, their trial actions and engagement, and third-party matched data to determine which customers will purchase and which ones will cancel - and it does this well before the trial period ends.
So, how do we take advantage of this to drive business impact?
Essentially, we can combine advanced C-API features (sending all consumer actions after stitching sessions and enriching identifiers) with predictive AI technology (assign a predictive value to all consumer actions, and only send the high-value actions).
With these working together, ad optimization algorithms within Meta, Google, and other similar platforms can optimize trials as if they already know which trials will lead to conversions, and find more purchasers displaying those behaviors.
To make your try-before-you-buy and free-trial-signup more effective in attracting high-value sign-ups that eventually convert, make sure to implement the following -
1) Improve Data Collection & Identification:
Ensure you collect persistent identifiers (like email and phone numbers) and verify them during the signup process.
Store marketing click & pixel identifiers to link ad clicks with user actions and signups.
Use behavioral data (pre-signup quiz or survey responses) to segment users and engage them in a personalized way, improving marketing and product fit.
2) Optimize Marketing Attribution:
Implement multi-touch attribution models to accurately track and attribute the impact of your paid social channels.
Use advanced C-API solutions to enrich later events with first-touch identifiers, enabling proper attribution to initial ad campaigns.
3) Leverage Predictive AI:
Utilize predictive AI models to predict the value of sign-ups based on data collected from source channels, onsite activity, and user engagement during trial periods.
Focus on optimizing ad campaigns by sending high-value consumer actions to ad platforms, improving targeting and conversion rates.
4) Monitor and Adjust Trial Sign-Up Strategies:
Regularly analyze consumer preferences and loss data to refine your trial offerings and adjust your marketing approach based on the insights gathered to reduce wasted spend and improve overall conversion rates.
At Angler AI, we’ve created the first Predictive Conversions-API (C-API) solution, and it's driving huge results for try-before-you-buy brands like Wantable.
If you want to leverage the predictive capabilities of Angler’s AI models to identify high-value sign-ups that actually convert, helping you increase the effectiveness of your marketing campaigns on ad platforms like Meta, Google, TikTok, and similar, make sure to take advantage of our free trial and test to see for yourself how your campaigns can result in increased revenue from your marketing efforts.