The Link Between Acquisition Campaigns and Product Metrics

Customer acquisition cost is one of the most important metrics of any company, especially those providing B2B services or SaaS products. The goal is to acquire users through cost-effective channels, reducing the resources needed to expand your customer base while ensuring the longevity of the customer-company relationship.

But not every acquisition is equal.

While most optimization techniques focus on reducing upfront costs and increasing immediate conversions, it is essential to consider the long-term value and behavioural patterns of acquired users.

Understanding and optimising the relationship between acquisition campaigns and product metrics is critical for sustainable growth and retention. Through this lens, we can define the importance of acquiring 'quality users' and analyse how product metrics can significantly influence acquisition strategies.

Defining a Quality User

In acquisition, many companies focus on quantity. The more users that convert, the better. But for sustainable growth, the quality of the acquired customer matters far more.

The quality of a user is defined by a few key metrics:

• Engagement: Regularly interacts with your product, indicating satisfaction.
• Revenue potential: Open to repeat purchases or premium offerings.
• Brand advocacy: Promotes your product through word-of-mouth, amplifying organic acquisition.
• Product fit: Has a need that aligns with the product’s value proposition.

All these things contribute to a customer's lifetime value (LTV), a crucial metric that can help understand each user's long-term impact and profitability. But, optimizing for LTV can be misleading if it is the sole focus.

Examining product metrics can provide a more nuanced view of user behavior, leading to a more granular optimization strategy.

How Product Metrics Impact Acquisition Strategies

So, how do we use product metrics to inform and optimise our acquisition strategies?

The North Star Metric

A North Star Metric is the single metric that best captures your product's core value to customers. It's a key signifier of a business's long-term growth and success. By focusing on this one thing, companies can align cross-functional teams around a unified goal directly tied to quality users.

For a SaaS product, this might be monthly recurring revenue (MRR), or for a social media platform, it might be daily active users (DAUs).

When designing acquisition campaigns, the North Star Metric helps to determine the type of users who will contribute to this growth. It allows marketing teams to tailor their strategies and messaging toward prospects most likely to engage.

It also helps evaluate the effectiveness of different acquisition channels and campaigns, focusing on quality rather than just quantity.

Channel-Product Fit

Every product has certain channels that work best for its acquisition. These channels are where a company's target users frequently engage and can be most effectively acquired. The key is identifying and leveraging these channels to get the maximum return on investment.

Channel-product fit involves mapping product features and benefits to the strengths of each channel, whether it's paid advertising, content marketing, email marketing, social media, or any other medium. This alignment ensures that the acquisition efforts resonate with the audience and lead to better conversion rates.

Sales Funnel and Event Tracking

A user’s journey from initial awareness to loyal customer requires a roadmap called the sales funnel. It breaks down into distinct stages, with each representing a pivotal step in the conversion process. Different sections carry different objectives and key results (OKRs) that guide optimization efforts.

Top of funnel (TOFU) focuses on awareness and reach. The primary goal here is to cast a wide net to capture as many leads as possible. OKRs for this stage are typically related to user impressions or website visits.

The middle of the funnel (MOFU) emphasises engagement and consideration. You want users to interact with your product or service, which means OKRs might include:

• Time spent on the website
• Pages viewed
• Product demos requested
• Content downloaded

Finally, at the bottom of the funnel (BOFU), the user is close to a purchasing decision. The OKRs become more conversion-centric, focusing on sign-up rates, completed purchases, or subscriptions.

Event tracking throughout these stages allows for precise measurement and analysis of user behavior. By tagging key interactions within the user journey, marketers can understand how effectively each stage is driving users toward a purchase.

Naming Conventions

The data gathered from event tracking is only valuable if properly categorized. Naming conventions in UTM parameters are critical for accurate tracking and analysis of acquisition campaigns.

Here are some common mistakes to avoid:

• Inconsistency: Simple mistakes like using “sping_sale” on one channel and “SpringSale” on another make it difficult to aggregate and compare data.
• Lack of clarity: Vague terms like “utm_campaign=january” or “utm_medium=social” do not provide enough detail to analyze the data.
• Complexity: Overly complex or lengthy parameters can also be problematic. It should be simple and follow with a pre-established pattern.

Here’s an example of a UTM code that follows best practices.

&utm_campaign=2024-01-30_META_Retargeting_Audience01_BOFU

Breaking down the elements we have:

• 2024-01-30: This indicates the specific date of the campaign launch, which is helpful for time-based tracking and comparisons.
• META: This is the internal code indicating the channel used, in this case, Meta advertisements.
• Retargeting: This indicates the strategy used for the campaign. In this case it is retargeting, connecting with users who have already interacted with the brand or product.
• Audience01: This defines a specific audience segment, which helps in understanding which groups are being targeted and how they respond.
• BOFU: This indicates the campaign is tailored towards users in the decision stage, aiming for conversions like purchases or sign-ups.

By balancing clarity and complexity, the data is now a valuable source of information. Anyone in the organization who reads it will understand when the campaign was launched, its goal, who it targeted, and how it fits into the user journey.

Attribution

Determining the value of each event in a customer’s journey is a complex task. Different attribution models assign value to touchpoints in unique ways, and the choice of model can significantly impact your understanding of campaign performance.

Last-Click

The last-click model attributes full credit to the final touchpoint before conversion. This model tends to favor bottom-funnel tactics and can undervalue earlier interactions' role in leading a customer toward that final decision.

For instance, an ad the customer clicked on a month ago that introduced them to the brand for the first time may receive no credit, even if it played an essential part in the purchase decision.

First-Click

The opposite model gives all credit for the conversion to the first touchpoint. This can be useful for understanding what channels effectively drive awareness, but may neglect the other interactions that nurture a prospect toward a sale.

Linear

The linear model splits the credit for a conversion equally across all touchpoints. It acknowledges that each step a customer takes contributes to the final decision. However, it also assumes all interactions are equally important, which may not always reflect the truth.

Time-Decay

Time-decay attribution models assign more credit to touchpoints closer to conversion. It is based on the logic that the closer a user gets to conversion, the more influential each touchpoint is. While this provides a weighted approach, it can still undervalue early engagement.

Position-Based (U-Shaped)

Position-based attribution—sometimes called U-shaped—gives more credit to the first and last touchpoints. Typically, they receive 40% of the credit each, while the remaining 20% is split between the other interactions.

The Acquisition Feedback Loop

Acquisition campaigns and product metrics exist in a state of constant interplay, with each informing and improving the other. This feedback loop allows for continuous refinement and optimization of marketing strategies based on actual user behavior.

Ideal Customer Persona

It starts with defining your Ideal Customer Persona (ICP). This detailed profile represents your most valuable customers, who benefit most from your product. Your ICP should inform every part of an acquisition strategy.

Over time, as you collect more data on your users, you can refine your ICP. Each interaction and conversion is a chance to validate or update the assumptions you’ve made about your ideal customers. Perhaps specific features are more popular with certain demographics, or pain points aren’t as pressing as originally thought.

Personalization

With a well-defined ICP in place, you can personalize acquisition campaigns to address the specific desires of those high-value users. By tailoring the experience to match the expectations of your ICP, conversion rates should improve.

The data from these personalization efforts feeds back into your segmentation and targeting strategies, evolving your ICP profile even further.

Quality

By targeting your ICP and providing them with personalized experiences, you are optimizing a campaign for quality users. You will start to understand which acquisition strategies lead to ongoing engagement, brand advocacy, and your North Star Metric.

Final Thoughts

This symbiotic relationship between acquisition campaigns and product metrics is intricate and invaluable. In crafting and revising your marketing efforts, remember that each user carries a trove of data that can inform future campaigns.

By diligently analyzing the link between how users are acquired and how they interact with the product, you can not only meet the market's needs but anticipate and exceed them.