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The customer journey is complex—and challenging to trace. It is a winding road laden with side streets and pit stops. Most consumers typically use a mix of online and offline channels along their journey to conduct research, compare products, and, ultimately, transact. A recent Google survey found that 60% of consumers take at least six actions before they make a purchase.
For many consumers, one action is picking up the phone. Invoca’s research shows the telephone is the preferred communication channel for more than two-thirds (68%) of customers who are considering a high-stakes purchase, like a car or health insurance, especially when they have questions, or they’re seeking customer service.
It’s tough enough to measure marketing attribution across an array of digital channels, let alone offline ones, like the phone. This guide is intended to help you with the process. The basics, benefits, and best practices that follow can help you create and maintain a robust marketing attribution model that can capture attribution from all critical sources.
First things first, let’s define what we mean by marketing attribution: It is a process businesses and their marketing teams can use to determine which channels, campaigns, or messages contribute to conversions. The insights gained from marketing attribution can be used to optimise campaigns and increase marketing ROI.
Why Is Marketing Attribution Important?
If you are a typical marketer, you deploy assets across many channels. Sometimes, the pace at which you roll out initiatives is so rapid that it’s hard to track which assets work and which don’t.
A marketing attribution model provides clarity on the effectiveness of assets and channels, particularly which ones are driving conversions.
Understanding where, when, and how conversions are happening, including the marketing touchpoints that have the most impact on your customers, is a significant factor in your ability to focus and optimise marketing strategies to boost ROI.
There are 10 major benefits that all companies can experience from having a strong marketing attribution model.
It is a constant battle for marketers: Meeting high expectations for marketing performance while working with limited resources. Showing a positive ROI can encourage funding decision-makers to loosen the purse strings or, at the very least, keep your marketing budget stable.
Accurate marketing attribution helps marketers identify their most profitable marketing actions so that they can focus resources and plan better revenue-producing campaigns.
Having clarity around what’s working and what’s not in a marketing campaign means you can more easily optimise marketing spend by allocating budget to the most effective channels and campaigns. You can also eliminate wasteful ad spending.
If a cost-per-click (CPC) Facebook ad campaign delivers twice as many conversions as a more costly display ad campaign on a local website, dumping display ads to put more resources into Facebook ads makes sense. You can make these cost-saving changes as quickly as the data is turned around, sometimes in real time.
Marketing attribution models help marketers more accurately map the customer journey. You can see which touchpoints are driving positive interactions. A better understanding of the customer journey also leads to enhanced customer engagement strategies because you are more “in tune” with your customers.
More definitive attribution leads to more informed budgeting decisions across marketing channels. When you know which channels are performing well, you can confidently assign more resources to those channels.
Access to accurate performance data can also enable the dynamic allocation of assets. That means assigning assets in real time based on attribution data highlighted by the model.
Marketing attribution data doesn’t just save you marketing dollars. It can prompt the adjustment of campaign tactics for better performance. That, in turn, can help you generate more revenue while also creating a more efficient and effective marketing program.
Continuous review and testing within the marketing attribution model will provide attribution insights that marketing can act on to build better campaigns with greater impact.
Data is the key to making well-informed, strategic decisions in today’s business world. That includes attribution data.
For instance, if your attribution data confirms that customer phone calls convert to revenue 10 to 15 times more than customer web leads, that would suggest your marketing team and your customer service agents need to be trained to handle more phone calls. You may also want to redirect some resources to beefing up call-handling capacity and use phone numbers more often in marketing assets.
Marketing attribution data can also highlight where channels interact to achieve marketing goals, so you can develop a more cohesive and impactful marketing strategy.
Consider this example: A customer scanning Instagram is targeted with an ad that offers health insurance. They click on it, but they don’t take their journey further. Later, they convert from a retargeted ad from the insurer, which they encounter on Facebook. Since the initial touchpoint served the cookie that enabled the retargeting, the cross-channel marketing strategy worked.
When the health insurance marketing team sees this data in their marketing attribution model, it prompts them to create a formal campaign that targets customers who use both Instagram and Facebook.
Personalisation is crucial to modern marketing success. As McKinsey & Co. pointed out in a report on the topic, companies excelling at personalising messages generate 40% more revenue than those that don’t. Personalisation leads to higher conversion rates and, not just more sales, but larger sales. It also boosts customer satisfaction.
Attribution insights from your model can help you develop more targeted and personalised marketing messages. So, don’t ignore the trends you see when tracking attribution. Use them to serve up relevant product or service recommendations to customers and create targeted promotions or triggers based on customer behavior.
Want to hold your marketing team accountable for their decisions and performance? A marketing attribution model does that by clearly and objectively showing your team the outcome of their efforts.
Use attribution as a tool to show the team when a strategy is clearly hitting the mark so that they can double down on their success. Also, use attribution data to make a clear case for pivoting quickly away from tactics that are falling short. (Sometimes, it’s hard for marketers to abandon campaigns until they see hard evidence that their ideas aren’t working.)
With marketing attribution, you can see better execution of current marketing activities, and your team will be more effective in planning future strategies and campaigns, too.
The last top benefit of marketing attribution builds on the point made above: It can enhance your long-term strategic planning.
When you use tools like AI and predictive analytics to inform your marketing attribution efforts, you can better identify where and when conversions are happening. And that means you can more confidently forecast trends that may impact future conversions.
Being ahead of the consumers — and your competitors — is certainly more advantageous than trying to chase them.
We’ve painted a rosy picture of marketing attribution so far, but nothing in business comes without challenges. We’d be remiss if we didn’t point out some potential slip-ups that could derail your pursuit of an optimised marketing attribution model. But by being alerted to them here, you should be able to navigate them later!
Data silos can significantly interfere with marketing attribution by fragmenting the data needed to accurately track and analyse customer journeys. They can lead to issues such as:
Integrating systems, standardising data formats, and promoting collaboration across departments can help to break down data silos. This will lead to more accurate and actionable marketing attribution, ultimately driving better decision-making and ROI.
Consumers frequently flit between their computers, laptops, mobile phones, and other devices like TVs and even gaming consoles along their customer journey. It’s tough, but not impossible, to track them across so many devices. A customer might begin a transaction on their desktop, head out to a meeting and complete a purchase using an app on their phone or tablet.
Marketers can overcome the cross-device tracking conundrum by issuing a unique ID to each customer. This is typically done at login using the consumer’s email address. Once a single user ID has been issued, you can track that user across multiple devices and platforms and use tools like Google Analytics to sort through the data to enhance your attribution model.
Today’s customer journey isn’t just complex because of the many apps and devices that consumers use. Most customer journeys start with initial research online but move offline to a phone call when the customer wants to transact, especially if they are making a large purchase.
It’s impossible to bridge the online-offline gap in attribution without collecting offline data. If you use a software platform like Invoca, which tracks, records, and analyses phone conversations at scale, you can successfully bridge the gap, enriching your attribution data with insights from the entire customer journey.
Another major challenge to gathering complete marketing attribution data are the many privacy laws, such as the European Union’s General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA) in the U.S., which affect how businesses collect and use customer data. Financial penalties for compliance missteps can be harsh.
You can navigate regulatory compliance mandates more confidently when you know the vendors in your tech stack are also fully compliant with relevant requirements. Check that they maintain certifications with the data privacy regulations that your business must comply with.
A constant challenge for accurate marketing attribution is the changing nature of consumer behavior. Sometimes, it seems as if it can shift on a dime.
Take consumer behavior in the automotive sector. Just two years ago, car subscriptions barely existed; today, there are at least 10 major players offering car subscription services, including Porsche and Volvo. So, instead of consumers buying or leasing cars, many are renting them for the long term or swapping models frequently.
Data suggests that a third of car buyers might like to try a subscription model in the next few years, which means car manufacturers and dealerships may have to pivot. They may need to update their business model and, perhaps, update their attribution models, too.
Regular analysis of your marketing attribution model to gauge where and when transactions are happening can help you stay nimble in response to changing consumer behaviors.
There are many models for marketing attribution; deciding which one is best comes down to your specific goals. To help you choose, here’s a closer look at some commonly used models and their pros and cons.
First-touch attribution assigns 100% credit to the marketing campaign that initiates the very first interaction somebody has with your business. This model ignores the campaign that ultimately drove the conversion as well as each interaction after the initial touch.
In last-touch attribution, 100% of the credit goes to the marketing interaction driving the conversion. Marketers using this model will gain insight into campaigns that have the highest conversion rate but lose sight of any influences leading up to the conversion.
Unlike first- and last-touch attribution, these four main multi-touch models consider multiple touchpoints along the customer journey to deliver a detailed perspective.
The linear attribution model is the first step toward multi-touch attribution. This model assigns credit evenly to every marketing touch throughout the customer journey. If there are 10 touches, each will receive 10% of the credit. When there are five touches, each will receive 20%.
The time decay model is another step forward in multi-touch attribution analysis. Time decay assigns the most credit to the interaction that resulted in a conversion. Touches leading up to the conversion event receive less value the further back they are from the conversion.
The position-based attribution model combines the best features of the linear and time decay models. This model assigns 40% credit to the first and last touch, with the remaining 20% being portioned out evenly to every other touch.
W-shaped attribution gives equal credit to first touch, lead generation. and opportunity generation touchpoints. It distributes the remaining 10% credit to all other touchpoints.
Opportunity generation occurs when a consumer re-engages with a brand following a first touch and lead generation and makes a purchase or converts. For example, if the consumer receives a digital ad (first touch) then signs up for a mailing list (lead generation) and clicks on a link in a follow-up email and makes a purchase, that’s opportunity generation.
Want to know how other marketers handle marketing attribution? Here are nine best practices we’ve gathered to help you succeed at getting the most from this process.
Start off on the right foot by picking the attribution model that works best for you. Look for a model that aligns with business goals and fits into your marketing strategies.
For example, if your marketing team only cares about qualifying leads, the first-touch attribution model might be all they need. If your team is looking to get more granular insights from touchpoints throughout the journey, determine which one of the multi-touch models fits best.
Regardless of which model you choose, it must run on high-quality, accurate data to enable reliable and meaningful marketing decisions. At the very least, you must remove duplicative and irrelevant data and maintain data in a consistent, standardised format for ease of analysis.
That doesn’t mean relying on a single source of data or marketing channel, either. Multiple sources enrich your insights, while relying on just a few data sources can skew results and make the process of marketing attribution worthless.
If you use a lot of marketing channels, you must capture data from all of them to unify the customer journey and strengthen your marketing attribution strategy. The problem is that since you’re gathering information from diverse channels and sources, data may not exist in the same format. It may be numerical and quantitative or textual and qualitative.
There are automated tools, like Oracle Data Integrator, Boomi, and Qlik, that integrate data into a standardised database, data warehouse, or data lake. (These tools automatically scrub data, too, ensuring you don’t duplicate results.)
You can also smooth this process by using tools that integrate into your tech stack and standardise data. Invoca’s call tracking software, for example, integrates with other everyday marketing tools like Salesforce Sales Cloud, Google Analytics, and Adobe Experience Cloud, as well as popular channels like TikTok, Facebook, and Instagram, to deliver effective data without the need for additional data integration.
It’s always good practice to create a framework for assessing how your model performs so that you can review and update the model as needed.
Also, make sure to add any new marketing channels to the model to capture as much relevant data as possible. So, for example, if you’ve embarked on an Instagram campaign since developing the model, add the data into the model to see if attribution is affected.
It’s also crucial to update the model if your marketing goals change, such as if you require more granular insights and move from a focus on lead generation to touchpoints further along the customer journey.
If you want even deeper insights from an attribution model, consider incorporating some of the existing key performance indicators (KPIs) your team is already tracking. One of the most useful is Customer Lifetime Value (CLV).
CLV reveals the dollar value of a customer over time. So, if a customer spends $1,000 on your product annually, and you expect them to remain a customer for at least four years, the CLV of that customer is $4,000. If your upfront cost to acquire that customer is more than $4,000, you have a problem.
Incorporating CLV into attribution provides insight to help reduce customer acquisition cost (CAC) and increase revenue by focusing on customer attributes that drive better responses.
Education is a critical part of any marketing attribution strategy. Your team must be confident in understanding how the model works, how it impacts marketing decision-making, and how it applies to their everyday work.
The attribution model should be seen as an insightful resource that everyone can use to make better marketing decisions. Set up a training program that fits your team’s expertise level and pace of learning. You can use online resources, classes, webinars, or self-learning.
Most important, don’t “set and forget.” Ongoing training is much more valuable than one-off sessions and can boost your team’s learning and development.
Online conversions are easy to track digitally, so phone data is often overlooked. But with artificial intelligence (AI) in the attribution tools mix, that’s changed. Now, phone calls can be captured and analysed at scale, just like online activity.
Why do you need data from phone conversations? Well, our research shows that 68% of consumers still prefer to speak to someone when making a high-value purchase. Those callers have high intent, and they often convert faster than digital customers.
Call tracking tools like Invoca get granular attribution data from phone calls that can be combined to create a more complete picture of a caller’s digital journey before they picked up the phone. This information includes their session data and the ads, campaigns, keywords, and webpages that prompted their call. This holistic view of the customer journey allows you to better understand how your marketing generates phone call conversions.
Continuously testing and refining your attribution model is essential to improving its accuracy and effectiveness. As marketing landscapes evolve, so do customer behaviors and the paths they take to conversion. By regularly testing and iterating, you ensure that your model stays aligned with these changes, providing more reliable insights.
One effective approach is A/B testing different elements of your attribution process. For example, you can test the impact of different attribution windows — comparing a seven-day window against a 30-day window to see which time frame captures more meaningful interactions. Another strategy is to experiment with various weightings for touchpoints. A linear attribution model might be compared against a time decay model to determine which better reflects the value of each customer interaction.
Testing should also extend to the tools and data sources you use. For instance, try integrating new data points, such as offline conversions, to see if they enhance the model’s accuracy. The goal is to continuously fine-tune your attribution model, ensuring it not only reflects the current customer journey but also drives smarter marketing decisions. Through regular testing and iteration, your attribution strategy will become more precise and impactful over time.
Always remember that whenever you collect personal data for marketing purposes, you must adhere to all relevant data protection and privacy laws, such as the GDPR and the CCPA. If you are in the healthcare sector, you must follow Healthcare Insurance Portability and Accountability Act (HIPAA) guidelines.
As noted earlier, you can meet regulatory standards more confidently by knowing your vendors involved in data collection, analysis, and transmission and confirming that they are certified and compliant with relevant regulations. Using tools that are already GDPR, CCPA and HIPAA compliant, like Invoca, helps your business stay compliant with privacy regulations while conducting marketing attribution.
A marketing attribution model is essential to building a winning marketing strategy, enhancing overall decision-making in the marketing function, and “defending your spend.”
To create a robust model, you need attribution for all conversions, not just the ones you track online. Using a tool like Invoca makes getting attribution for phone call conversions as easy as online attribution. Invoca integrates with your existing marketing stack and analytics, fitting seamlessly into your attribution models and workflows to help maximise your marketing ROI.
To learn more about how AI-powered tools can improve the accuracy of marketing attribution for offline conversions like phone calls, see these additional resources from Invoca:
When you’re ready, contact us to set up a free, customised demo to see our technology in action and discover how it can transform your marketing performance.
