It’s an age-old problem.
Retailer John Wanamaker is credited with saying, “Half the money I spend on advertising is wasted; the trouble is I don’t know which half.” He said that back in the 1800s, well before today’s mass media, social media and digital world. Yet, it’s as true today as then and likely even more so.
You need attribution analysis to understand what parts are working and what’s being wasted.
What is marketing attribution analysis?
Marketing attribution analysis identifies the actions users take across multiple marketing channels to evaluate effectiveness.
Today, most marketers are using several tactics to acquire customers. It’s common for ecommerce sellers to run PPC ads on search and social media, optimize for SEO, use affiliate marketing programs and run email campaigns.
When a conversion happens, which ones should get credit for the purchase? Marketing attribution tools can help uncover the insights you need to figure it out.
The importance of marketing attribution analysis in ecommerce
The benefits of a marketing attribution strategy include:
- Better understanding of the customer journey
- Evaluating sales channels and campaign effectiveness
- Personalizing marketing efforts based on interactions
- Identifying touchpoints that build loyalty and drive repeat purchases
- Determining and tracking return on investment (ROI)
Attribution analysis marketing will become even more important in a down economy or as consumer behavior changes. You need to know what marketing touchpoints are working across the customer journey and what’s missing the mark to optimize marketing performance and eliminate wasteful digital marketing spending.
As customer acquisition costs (CACs) continue to escalate, maximizing spending on your marketing channels becomes crucial to delivering ROI.
The best ways to master marketing attribution analysis
There are several different ways you can leverage marketing attribution analysis to grow your business. We've put together six best practices on how you can leverage analytics to help grow your ecommerce business.
1. Implement a multi-touch attribution model
Multi-touch attribution improves conversion rates and reduces CACs for ecommerce brands. When you know where customers came from and what led to conversions, your marketing team can better focus your advertising and marketing campaigns.
A unified analytics platform tracks the data you need to get an overview of the marketing customer journey across multiple touchpoints to make better decisions about sales channels and campaigns. This holistic view of multi-touch marketing helps the sales team work more efficiently.
2. Leverage advanced analytics tools
Effective attribution analysis marketing leverages the data you collect and analyze. Information captured from CRMs, Google Analytics and other tracking algorithms can provide significant insights into the path to conversion.
The best advanced analytics tools can define the net contribution of each channel and touchpoint to help you allocate your ad budget and focus your marketing efforts to maximize return. For example, you can calculate a customer’s propensity to convert before and after each engagement, showing the impact of an ad on the likelihood to convert and track changes as you refine ad copy.
3. Use data-driven attribution modeling
Businesses today can’t afford to rely on what worked in the past. Consumer behavior is constantly evolving. If you miss trends, you can miss revenue opportunities. Data-driven attribution modeling uses statistical algorithms to understand each marketing touchpoint and how to assign credit for conversions.
Data-driven attribution modeling outperforms traditional rules-based models to assign credit more accurately. Using techniques such as linear attribution, time decay or position-based attribution can help better evaluate performance.
4. Integrate marketing attribution models and automation
Typically, ecommerce brands utilize several different attribution marketing models, including:
The first-touch attribution model assigns all the credit to the first marketing channel a customer interacts with. It’s a simple and easy way to see how customers first interacted with your brand, but it ignores the cumulative effect of your marketing strategy that may have been the underlying reason for the sale.
First interaction attribution works well for single-channel marketers and brands that convert customers immediately. This model also works well for tracking which channels produce brand awareness.
Last touch attribution
The last touch attribution model assigns credit to a customer's last touchpoint before converting. If someone clicks an ad and makes a purchase, this model assigns all of the credit to the ad. This is a great way to track one-click purchases, but it can overestimate the value of the last touchpoint.
In the pre-internet days, the Yellow Pages often got credit for referring customers, but it was often the cumulative impact of marketing and advertising that built brands so customers chose them in the directory. In digital marketing, it often works the same. Someone may have seen an ad, email or content marketing piece you developed, done research about your product but then converted only after clicking on a social media post.
Last non-direct click
When someone comes directly to your website and converts, that’s great. However, it doesn’t always tell the story of the customer journey. In multi-touch marketing, marketers know that direct sales are also the result of multiple marketing efforts. Let’s say someone saw a social media post, clicked on it and signed up for your mailing list. After opening several of your email marketing messages, they went directly to your website and made a purchase.
In the first-touch model, the social media post gets credit for the sale. In the last-touch model, your website gets the credit. But what was the final piece that made them go to your website? The last non-direct click assigns attribution to the last engagement before visiting your website. In this case, an email marketing message.
This method provides more insight into which marketing channels led to a conversion, but it also tends to ignore the impact of touchpoints that came before the last non-direct click.
The linear attribution model gives credit to all of the brand touchpoints in the customer journey. So, if a customer clicked on a PPC ad, read an email you sent and visited your website, all three touchpoints would get equal credit for the conversion.
Linear attribution helps assign credit to every touchpoint and shows the impact of each marketing channel on the purchase. However, it can underestimate or overestimate the influence of any particular channel. It demonstrates the path to conversion well, but it does not help determine what provided the greatest influence.
The time decay model also spreads credit across touchpoints but weighs later touchpoints more heavily. The first engagement gets less credit than the last. This is an effective technique for finding the key touchpoints that led to the final conversion while still giving credit to earlier engagement that may have contributed to the sale.
It’s not as effective for a business that has short sales cycles.
Position-based attribution splits credit, putting more weight on the first and last touchpoint to reflect the customer journey. For example, 40% of the attribution might go to the first engagement, where customers became aware of your brand, and 40% to the last engagement, where they clicked and converted. The in-between steps, such as email marketing or social media posts, would get the remaining 20%.
Position-based attribution can work well for businesses that rely on multiple touchpoints before conversion but can also over- or underestimate the impact of messaging throughout the customer journey.
5. Experiment with A/B testing for attribution
A key to optimizing performance is to continue to test various combinations. Controlled experiments, such as A/B testing (split testing), can refine your attribution models. For example, you might split your targeted audience into smaller groups and apply different attribution models to see which produces the most accurate results. A/B testing is often used to test different email subject lines or preheaders, ad headlines and ad copy or content marketing topics, but it can also be used effectively to find the attribution models that work best for you.
6. Continuously monitor and optimize attribution methods
Ecommerce requires continuous monitoring and optimization. Not only do customer behaviors change, but your competitors are also making moves. You might have a great campaign run that suddenly becomes irrelevant in light of shifting views on issues, a competitor’s sale price or concerns over the economy.
As such, marketing attribution analysis needs to be an ongoing process to continuously validate the performance of your marketing and your attribution models.
Schedule a demo with a Unified Analytics expert now
Cart’s Unified Analytics makes your ecommerce metric actionable, simplifying and analyzing your data to produce the insights you need to grow your business. You can connect all your data from across the shopper journey using automated tools that you don’t need a computer science degree to use.
You don’t need to have experience with analytics to leverage Cart’s insights, which provide actionable recommendations to improve business performance. Conceding seamlessly to the most popular marketing and sales channels, Cart helps you maximize the ROI from your attribution analysis marketing.
Connect with Cart.com today, and let’s explore the opportunities to work together.