During my brief retirement at the start of 2020, I was delighted to be contacted by an ex-client, Julie Molloy, who I hadn’t been in touch with for many years. Julie heads up the marketing for a smart digital agency, QueryClick, based in Edinburgh. The agency’s big promise is that AI can be used to improve marketing attribution. In other words, it can help with the marketer’s biggest challenge – proving ROI, and demonstrating which activities contributed to it, and to what degree. I worked successfully with QueryClick for about 18 months before turning my focus back to electronics B2B work, but it was a fascinating experience, and I learned a lot. Out of curiosity, I thought I’d ask ChatGPT to explain a little about marketing attribution in B2B tech. Here’s what I gave it and what it produced.
INPUT: Write an article about marketing attribution in B2B tech
OUTPUT: In the world of B2B tech, marketing attribution is a crucial element of measuring and optimizing marketing efforts. Marketing attribution is the process of identifying which marketing touchpoints, channels, and campaigns are driving customer acquisition, engagement, and conversion.
The primary goal of marketing attribution is to understand the effectiveness of different marketing initiatives and to allocate resources to those initiatives that have the greatest impact on revenue and business outcomes. By understanding which marketing activities are contributing to revenue, B2B tech companies can make data-driven decisions and optimize their marketing strategies to drive growth.
Marketing attribution in B2B tech is particularly challenging due to the complexity of the sales cycle. B2B sales cycles are typically longer and involve multiple decision-makers, making it difficult to identify which marketing touchpoints are driving conversions. Additionally, B2B purchases are often high-ticket items, which makes it even more important to understand the impact of marketing efforts on revenue.
There are several different models of marketing attribution that B2B tech companies can use. The most common models are:
- First-touch attribution: This model gives credit to the first marketing touchpoint that a prospect engages with. This model is useful for understanding which marketing channels are driving initial awareness and interest.
- Last-touch attribution: This model gives credit to the last marketing touchpoint that a prospect engages with before converting. This model is useful for understanding which marketing channels are driving the final conversion.
- Multi-touch attribution: This model gives credit to all of the marketing touchpoints that a prospect engages with throughout the entire sales cycle. This model is useful for understanding the impact of each marketing touchpoint on the conversion process.
- Weighted attribution: This model assigns different weights to different marketing touchpoints based on their perceived importance. This model is useful for understanding which marketing touchpoints are the most influential in the conversion process.
B2B tech companies should choose the attribution model that best fits their business needs and goals. It’s important to remember that no attribution model is perfect, and B2B tech companies may need to use a combination of different models to get a comprehensive view of their marketing impact.
To implement marketing attribution, B2B tech companies should invest in the right technology and tools. Marketing automation platforms, customer relationship management (CRM) systems, and analytics tools are essential for tracking and measuring marketing efforts. By leveraging these technologies, B2B tech companies can capture data on each marketing touchpoint and use it to analyze and optimize their marketing strategies.
In conclusion, marketing attribution is a critical element of B2B tech marketing. It enables companies to understand which marketing efforts are driving revenue and make data-driven decisions to optimize their strategies. By choosing the right attribution model and investing in the right technology and tools, B2B tech companies can effectively measure and optimize their marketing efforts to drive growth and success.
I wonder how my marketing lecturer would have scored this if he’d given me the same task and I’d written this answer. It may not have won a distinction, but I have a feeling I would have scraped a pass. What do you think?