Unmeasurable Metrics in Performance: A Marketing Strategy Example
- 9 min
- 15.03.2024
Performance marketing excels in digitizing indicators so precisely that both SEO specialists and clients can see the effectiveness of each step. This allows for the calculation of whether advertising budgets are paying off, which campaign performed better, what needs to be corrected, and what can be improved.
However, even in such precise data analytics as financial reporting, there are special scenarios where some metrics require an unconventional approach. Let’s explore how this works and whether it’s possible to measure the unmeasurable.
How Performance Marketing Works
Let’s first give the most complete definition to dive into the details within the context of the topic. Performance marketing is not just a direction but a comprehensive promotion strategy. In performance marketing, you can see the results and measure KPIs even after a short period of time. This approach helps achieve real business goals without wasting budgets.
To make the strategy work, there are more than 30 different advertising effectiveness metrics. The essence of each is to show the ratio of the invested budget to the profit generated by a specific action.
Most Common Metrics in Advertising Campaign Payment
- CPC (Cost Per Click): Payment is made for each targeted click on a banner ad.
- CPA (Cost Per Action): Payment is made for specific user actions, such as purchases or registrations.
- CAC (Customer Acquisition Cost): Indicates the cost of acquiring a customer, helping determine overall campaign cost-effectiveness.
- DRR (Direct Revenue Return): The ratio of advertising campaign expenses to the revenue generated, calculated as a percentage.
We noted earlier that intermediate effectiveness indicators can be calculated in performance marketing. This is important because it allows for the assessment of work results at the beginning of strategy implementation, in the middle of the promotion campaigns, and at any other stage after implementing new tools and checking their effectiveness. The more accurate data available and the faster it can be obtained without waiting for the campaign’s end, the more the necessary indicators can be improved.
Contextual Advertising: A Key Direction in Performance Marketing
Contextual ads reflect users’ interests as they match their actual search queries. These settings are highly flexible and can be adjusted at any stage of an active campaign. This flexibility allows for tracking audience responses and making timely adjustments to improve campaign effectiveness.
Performance Metrics That Are Difficult to Measure
Despite the accuracy of analytics and the flexibility of settings, performance marketing has indicators that cannot be precisely quantified — making it impossible to create a detailed report on the advertising’s return on business goals. However, even in this case, SEO specialists clearly understand how to act: it requires considering the specifics of the interaction of ads with platforms, search engines, and user behavior factors.
It is important to determine the so-called «stop-factors», i.e. points or stages where this interaction is hindered, reducing the effectiveness of advertising.
Touchpoints with Users: Too Many. Large brands often face the challenge of tracking customer journeys across multiple sources—contextual ads, TV ads, outdoor advertising, social media, and more. This complexity makes it difficult to calculate the true advertising cost.
Decision-Making Path: Too Long. For expensive purchases, the decision-making process involves multiple steps, such as getting to know the product, building trust, and testing the product. In such cases, it is challenging to determine which channel led to the final purchase.
Purchase Format: Happens Offline. Products like cars and real estate are rarely bought online due to their high cost. While information can be found online, the final purchase decision usually happens offline, complicating comprehensive analytics.
Number of Applications: Too Few or Clearly Insufficient. For large B2B companies, where products are expensive and sales are infrequent, web analytics can be limited. Advertising investments yield results over a longer period, making immediate web analytics less relevant.
Calculating Unmeasurable Metrics: Digital Strategy Experience and Practice
Complex products with unique specifics require a tailored approach for each business. Over the years, we have developed numerous successful cases, allowing us to create bespoke marketing strategies. Here are some challenges we address:
- Insufficient data for a «classic» advertising campaign;
- Inability to implement analytics systems widely used in other cases;
- Strict privacy policies;
- Lack of integration with other tools — such as CRM.
Moving to a Specific Example
While we won’t disclose detailed client information, we can explain our project logic step by step.
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Client:
A large premium brand.
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Advertising:
Attracts several dozen targeted leads per year.
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Decision-making Path:
Takes several months on average, from the first contact to placing an order.
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Main Challenge:
Few conversions, direct or branded search queries, long gaps between visits, and no direct connection with initial advertising visits.
Stage One: Website Markup
This concerns all intermediate actions that the user takes on the website:
- Active interaction with the website for 60 seconds;
- Button clicks;
- Transitions to social networks;
- Visiting landing pages with services or projects;
- Viewing contacts;
- Downloading promotional materials;
- Communication in a website chat with a consultant.
Stage Two: Assigning Significance to Each Goal
This stage involves determining how much each action influences a purchase. The process includes:
- Uploading conversions by date;
- Comparing the dynamics of targeted requests and actual deals in the CRM.
- Is there an obvious relationship between events? Then the intermediate user actions have the greatest weight. Of course, we considered the possibility of error at the start of work, but this is also part of the specifics.
- Making adjustments, keeping in mind that the weight significance coefficients of user actions could be changed based on actual user feedback.
- And if the client indicated a specific section of the website in feedback? Then an additional coefficient of +10% is applied.
Stage Three: Forming the «Scoring» Indicator
The metric is formed as follows: goals are multiplied by coefficients and summed up.
S = Goal1*K1 + Goal2*K2 …
This way, we checked the hypothesis of the maximum scoring value. The more the target audience visits the site and performs specific targeted actions, the more final deals occur throughout the touchpoints journey.
Stage Four: Setting Up Dashboards
Dashboards help us monitor results, collect data, and form statistics. Adjustments are made as needed to refine the scoring model. Goals that don’t contribute to the desired outcome are excluded.
Strategy Outcome
Applying the coefficients proved effective, requiring minimal adjustments. The results confirmed our hypothesis: increased target audience engagement leads to more conversions and completed deals.
![Image](https://ds.team/wp-content/uploads/2024/03/3.jpg)
Final Conclusion
The number of actual deals was small, and the touchpoint chain included both online and offline interactions. Clear analytics in such conditions were not feasible, making direct optimization of advertising campaigns for deals challenging and potentially inaccurate. However, by considering all factors, we developed a robust working method that appropriately leverages these metrics.