As you may recall from a previous post, marketing attribution models are tools for distributing credit for a conversion across the various touchpoints of a customer journey. These models help marketers understand the effectiveness of different campaigns and channels by assigning value to interactions that lead to a sale or other desired action.
There are many different types of marketing attribution models, based on a company’s varying goals, and business needs. For example, a simple last-touch model might be useful for understanding immediate impact, while a multi-touch model is better for a holistic view of engagement.
Because customers interact with local businesses across multiple channels over time in a complex customer journey, multi-touch attribution models can be especially helpful in revealing which touchpoints are most valuable at various stages.
Today we’ll review multi-touch attribution models and how they can provide insights into which channels and campaigns are truly effective, enabling marketers to allocate their budgets most efficiently and improve their overall marketing return on investment.
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A multi-touch attribution model (MTA) is a marketing analytics method that distributes fractional credit for a conversion across the multiple marketing touchpoints a customer interacts with during their path-to-purchase. With research suggesting the average number of marketing touchpoints ranging from 6 to 8, MTA provides a more comprehensive understanding of how different components of the marketing mix work together synergistically to drive results. Unlike single-touch models (which credit only the first or last interaction), MTA recognizes that customer decisions are shaped by a series of interactions and aims to provide a more nuanced and accurate view of marketing effectiveness by assigning value to various touchpoints leading up to the conversion.
Multi-touch attribution can lead to a more comprehensive understanding of customer engagement with your brand; a higher level of optimization of your marketing mix; informed decisions that lead to more effective allocation of your marketing budget; and is particularly useful for businesses with complex sales cycles and personalized customer engagement, where a single interaction is rarely sufficient to drive a purchase.
Some of the more common multi-touch attribution models include:
Linear Model: This model assigns equal credit to every touchpoint in the customer’s path to purchase.
Time Decay Model: This model gives more weight and credit to touchpoints that occur closer to the conversion event, assuming recent interactions have more value.
Position-Based Models (U-Shaped, W-Shaped): These models assign significant credit to the first touch, the last touch, and potentially a key mid-funnel event with remaining credit distributed among other touchpoints.
Data-Driven/Algorithmic Models: These models use machine learning to analyze vast amounts of historical data and user behavior patterns to dynamically assign credit based on actual impact, offering a more sophisticated and personalized approach.
Some of the more popular platforms providing multi-touch marketing attribution include Google Analytics 360, HubSpot Marketing, and Amplitude.
Marketing attribution models, including multi-touch, can be powerful tools to help you optimize your marketing investments in alignment with your business and your customer’s journey, but there are challenges to multi-touch attribution including:
- Data Collection Complexity: MTA requires accurate and comprehensive data from multiple sources, which can be challenging due to data silos, cross-device tracking issues, and cookie restrictions.
- Difficulty Tracking Offline Activities: Digital MTA struggles to account for crucial offline interactions such as in-store visits, phone calls, and television and print advertising, leaving blind spots in the customer journey.
- Correlation Challenges: MTA relies on correlation-based data, meaning it observes patterns but cannot definitively prove that a specific touchpoint caused a conversion.
Despite these challenges, even with limited resources small businesses can utilize multi-touch attribution by focusing on simple, cost-effective strategies. The key is to start small, leverage accessible data, and choose a straightforward model that aligns with your business goals.
Multi-touch attribution models offer significant value to businesses by providing a clearer understanding of how various marketing channels contribute to customer conversions. Unlike single-touch models that credit only one interaction, MTA distributes credit across multiple touchpoints giving a more accurate picture of the customer journey and the effectiveness of your marketing in moving those prospects to becoming customers.
This insight helps small businesses make smarter marketing decisions, optimize their limited budgets, and focus on the channels that truly drive results. Ultimately, MTA empowers local businesses to compete more effectively through improved marketing engagement and maximizing return on marketing investment.
To learn more about multi-touch attribution models and how it can help your local business, we encourage you to give us a call at 603-352-5896 or email Advertising@SentinelDigitalSolutions.com.
We are experts in multimedia marketing and can help you build a compelling campaign that engages your audience and drives sales.
We’re here to help you succeed.
Disclosure: This post was curated with AI assistance.
Additional Resources:
- What is Marketing Attribution?
- Is Last-Click Attribution a Good Measure of Your Advertising Effectiveness?
- Can Marketing Analytics Help Your Local Business Succeed?
- Understanding The Customer Journey Toward Business Success.
- What is Multimedia Marketing and How Can It Help Your Local Business?
