Marketing goalposts tend to keep moving. Best practice and tool capabilities are constantly evolving. In the last two decades, we can pretty much boil it down to a shift from ‘spray and pray’ to a ‘track and stack’ approach.
Once upon a time, the only option for marketers was to invest budgets across different activities and take an educated guess at how that translated into sales. Today, with the marketing tools and measurement capabilities available, you can monitor campaign performance from the minute it goes live to understand what channels, initiatives, and messages generate the best results. This means you’re able to optimise and double down on what works.
Marketing attribution is the process of being able to track how certain messaging and channels are actually affecting your customers’ willingness and ability to make purchases. In other words, what’s engaging them and what obstacles are making them drop off?
For example, you might be running a really effective ad with eye-catching visuals and a value-driven tagline. It gets a lot of attention, but when users click through to your website, the UX is clunky, the CTAs aren’t clear, so a lot of people drop off before completing a purchase. Maybe your ad creative isn’t clearly conveying the benefits of your offering. Or maybe you’re focusing on posting to LinkedIn when more of your audience is on Instagram. Attribution is your means of diagnosing what’s working and what isn’t.
This is extremely useful because it informs a lot of strategic decisions. For example, are you spending time and money in the right places? Are you generating a lot of leads which aren’t translating into conversions?
Having this kind of visibility means you’re much better equipped to optimise marketing spend, improve ROI, and gain clearer insights into customer behaviour. This can be even more valuable in B2B marketing where sales cycles are longer and are more likely to involve multiple decision-makers.
Typically, in B2B marketing, advertising generates leads which are then nurtured by sales reps until a purchase is made. In contrast, B2C consumer paths tend to be more direct, especially in e-commerce, where leads funnel instantly through to purchases.
This longer consideration phase makes B2B attribution more complex, but also a potentially rich source of data. Here’s why.
B2B transactions typically involve multiple brand interactions across multiple channels. For example, a prospective client might first encounter your business through a LinkedIn post, then download a whitepaper from your website, attend a webinar, and – finally – make contact with a sales rep. Identifying which of these touchpoints is most influential in their decision-making process isn’t always straightforward.
New digital channels have created more opportunities to reach specific audiences. But that also means there’s a lot more to keep track of. In the past, B2B marketing might have focused more on offline channels like direct mail, trade shows, and print advertising. Now, the mix favours digital advertising, email campaigns, social media, and SEO. The good news is that digital channels are easier to track through to conversion. The challenging part is that there’s so much to keep track of.
B2B customer journeys are increasingly non-linear, as prospects engage with content at different stages. According to Gartner, customers typically exhibit a behaviour known as 'looping' during a B2B purchase, repeatedly revisiting various stages of their buyer journey. This includes steps like identifying their needs, sourcing a solution, browsing suppliers, and getting internal stakeholders onboard.
Poor attribution in B2B marketing can lead to misaligned strategies, where efforts and resources aren’t focused on the most impactful channels. This results in poor understanding of customer behaviour, inefficient ad spend, and – ultimately – lower ROI. For example, overvaluing the impact of last-click interactions while undervaluing educational content higher up the funnel. This can skew budget allocation away from crucial brand awareness efforts, impacting long-term customer relationships and sales growth.
So, you want to track customer journeys but don’t know where to start? There are many different means of attribution which vary in their level of detail and purpose. And some may be more suited to certain channels than others, or dependent on particular variables you might want to test.
Selecting the most effective attribution model in B2B marketing hinges on understanding the complexities of buyer journeys. Here’s what you should consider:
Longer sales cycles with numerous touchpoints may benefit from multi-touch models like Time-Decay or Position-Based attribution, which acknowledge multiple influential interactions.
Evaluate the role and impact of different channels in your marketing mix. For instance, if early-stage awareness is crucial, First-Touch or U-Shaped models might be more appropriate. For more conversion-focused strategies, Last-Touch or Time-Decay models could be better suited.
In many B2B scenarios, mid-funnel interactions such as demos or detailed consultations play a critical role. Models like Position-Based attribution, which assign significant value to these interactions, could be more suitable.
For highly non-linear customer paths, data-driven or custom attribution models can offer the flexibility and precision needed to account for various journey types.
If your B2B marketing involves a mix of offline and online touchpoints, consider an attribution model that can integrate data from both worlds, such as custom models or advanced data-driven approaches.
Make the most of advanced analytics tools and machine learning algorithms to gain deeper insights into how different touchpoints contribute to conversions, guiding you towards more sophisticated models like Data-Driven or Custom Attribution.
Continually review the performance of your chosen model against actual sales data and be ready to adapt. The dynamic nature of B2B markets means that what works today might need adjustment tomorrow.
To ensure effective attribution, here are some key tips that can guide your strategies and enhance the precision of your B2B marketing efforts.
Multi-touch attribution models, like Position-Based or Data-Driven models, consider multiple touchpoints in a customer's journey. Unlike last-click attribution, which credits the last touchpoint before conversion, multi-touch models distribute credit across several touchpoints, providing a more holistic view of what's driving conversions.
Data-driven models, especially those enhanced by machine learning, dynamically analyse and assign credit to touchpoints based on their impact, adapting to evolving data patterns for improved insights. These models can be very effective in leveraging your data to understand how each touchpoint contributes to your final goal.
Integrating your marketing efforts with CRM systems like HubSpot or Zoho allows you to track long-term customer value, not just immediate conversions. This is helpful in understanding which marketing efforts attract customers with high lifetime value and in making strategic decisions to foster long-term customer relationships.
Ensure that you have robust systems for tracking and collecting data across all channels. This includes setting up proper UTM parameters, using analytics tools effectively, and ensuring data consistency.
A comprehensive view of the customer journey involves integrating offline data (like in-store purchases, phone calls, etc.) with online data (like email open rates, ad interactions, and eCommerce transactions). This gives you a more complete picture of your customer interactions and how different channels work together, which improves the accuracy of your attribution model.
Similarly, with users often switching between devices, it's important to track and attribute conversions across different devices. This can be challenging, but it’s crucial for a complete understanding of the customer journey.
By mapping user interactions from initial contact through to conversion and beyond, you get a complete view of the customer journey. This is how you can pinpoint which advertising efforts contribute the most to customer acquisition and retention.
Combining insights from advertising data and CRM enhances customer segmentation and targeting. This results in more effective advertising campaigns, as messages can be tailored to specific segments based on their behaviour and preferences, ensuring greater impact from your marketing efforts.
In the years to come, B2B marketing attribution is set to become even more nuanced and sophisticated. The integration of marketing tools and platforms will become more streamlined. The advancement of machine learning, in particular, will revolutionise how we track, report, and derive insights from data, making attribution more accurate and accessible.
In an increasingly unstable economic environment, the ability to pinpoint exactly where marketing efforts are most effective is more important than ever. Companies that effectively understand their customer journeys can allocate resources more efficiently, adapt quickly to market changes, and ultimately drive better ROI.
In this evolving landscape, it's vital for B2B marketers to adopt sophisticated attribution models and embrace advanced tools. Doing so not only enhances current campaign effectiveness but also prepares businesses for future market shifts.
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