Attribution modeling in B2B marketing – identify how channels influence conversions

The most common and traditional way to measure digital marketing is the last-click attribution model. It gives 100% of the credit to the channel the customer clicked immediately before conversion.

Imagine a typical scenario:

1. A marketing manager sees your company's expert video on LinkedIn and becomes interested.
2. A week later, they read your blog article through organic search.
3. A month later, they are ready to buy, Google your company name, click a branded Google Ads ad, and submit a request for proposal.

If you use the last-click model, Google Ads gets all the credit. Based on that data, you may make a damaging decision: stop the "non-working" LinkedIn advertising and content production, and move the entire budget to Google Ads. As a result, the flow of new customers dries up because you removed the engine at the top of the buying journey that originally created interest.

The last click does not tell the truth; it only shows the finish. It distorts the real ROI of marketing and prevents the company from scaling growth profitably.

In B2C, a purchase decision can happen in minutes because of a strong Instagram ad. In B2B marketing, the situation is completely different.

The B2B buying journey is long and complex. It often involves several experts and decision-makers. The decision cycle can last months or even more than a year. That is why customer journey measurement cannot be based on isolated, individual touchpoints. Success in B2B requires understanding the whole buying journey from the first brand encounter to the closed deal.

To understand the true effectiveness of your marketing, it is important to know different approaches. The right attribution model depends on your company's goals and sales cycle length:

• First-click model: Gives all credit to the channel that first brought the customer to the website. Useful for measuring brand awareness, but leaves the later journey in the dark.
• Linear model: Splits value evenly across all touchpoints. Gives a broader view, but does not account for some interactions being more valuable than others.
• Time decay model: Gives more weight to touchpoints that happened closest to conversion.
• Position-based model: Emphasizes the beginning and end of the buying journey, distributing the rest of the value to middle-stage touchpoints. This is often a usable basic model for B2B companies.
• Data-driven model: The most modern approach. AI analyzes a large amount of data and dynamically calculates the actual influence each channel and campaign had on the buying decision.

Want to know which channels and content really influence your customer acquisition?

Do not make decisions based on incomplete data. Find out the true return and bottlenecks of your marketing.