The celebrated Forrester Research institute unequivocally states that “traditional one-to-one, last-touch methods of allocating demand to marketing efforts are outdated and lead to a suboptimal marketing mix. Customer Intelligence (CI) professionals must adopt a cross-channel attribution model in order to optimize marketing budgets, accurately calculate customer value and acquisition costs, and develop a holistic view of the marketing ecosystem.” They aren’t mincing words there. But don’t worry. We feel your pain.
We’ve heard all the objections before: cross-channel attribution is too complicated, there isn’t enough data across platforms, and it’s simply more work than it’s worth. … Which is why we’re here to debunk those myths and help you realize that cross-channel attribution is easier (and more valuable) than you ever imagined. If you read our blogs, you know we believe in cross channel-marketing, so it shouldn’t surprise you that we are a champion for cross-channel attribution.
Customers expect a highly personalized marketing experience, and we can’t give that to them if we don’t understand how and why they invest time in certain platforms or content types. Your accounting department probably wouldn’t be too thrilled to find out you were using an inaccurate, outdated methodology to calculate your ROI and forecast your budget for next year either. Here are a few objections we often hear from our clients when faced with this reality … and how we have helped them overcome their challenges.
Objection: “Last-touch attribution is good enough…”
Last-touch attribution, or giving sales credit to the last platform a customer engaged with prior to purchase, may seem like the path of least resistance, but it simply isn’t accurate. For budding analytics teams, last-touch attribution is a quick way to start collecting directional data without needing too many tags or complicated methodology. Unfortunately, many touch points get excluded or underweighted because they don’t always represent the point of sale, even though they play a critical part of your customer journey. Last-touch is certainly better than nothing and will get your team started, but often misses the bigger picture (your email team will probably agree, since they are almost always a first or early customer touch point). We often tell clients who are just beginning their journey to a more accurate attribution model to start small. Let us help you roadmap your path to cross-channel attribution by setting milestones that will slowly and thoughtfully expand on your last-touch model. By adding one data point at a time, your team can fine-tune the accuracy and usefulness of each piece of new information before expanding your program.
Objection: “Cross-channel attribution isn’t accurate because offline data doesn’t exist…”
The notion that we can’t track or stitch together customer behavior both on- and offline may have once been true, but that’s no longer the case. Seasonality, competitor presence in market, event marketing, word of mouth, and hundreds of other offline variables are — yes — more difficult to track, but can be evaluated through the use of digital tools. For example, we recommend assigning a special hashtag, social media filter, or promotion to an in-store event or offline campaign to help you gauge the success of the many channels working together to make that experience a success. As offline data improves through the use of GPS signals, beacons, and AR breakthroughs, this pain point will continue to fade away. By ensuring your other channels are accurately tracking and that you are prepared to enhance offline data, you’ll be ahead of the curve and competition.
Objection: “We already use programmatic advertising software and don’t need additional tracking…”
Don’t mistake the ease and efficiency of programmatic bidding and ad placement with understanding which channels are pulling the most weight. PA software is a great tool that uses data from a variety of sources to optimize your ad placements and spend, but it doesn’t tell you enough about your overall channel performance to make informed decisions about the types of content or campaigns you want to beef up on — it simply makes the most of what you’ve got. Cross-channel attribution should affirm that your digital ads are doing their fair share of work, but will also reveal where guests aren’t spending time and provide insight into how you can improve your holistic strategy. Depending on how robust your data is, we often suggest businesses start with building a flawless analytics program and then adding programmatic advertising because good customer insights will elevate all your campaigns — even automated ones. Let us help you find a balance between your programs to maximize success.
Objection: “It won’t really change how we go to market…”
The more you know about your customers, the more you can anticipate their needs. Knowing that your most valuable customers often respond to email promotions, but purchase in-app; or that your Instagram account is driving people to your best YouTube tutorials; or that most people browse your content on their mobile devices, but purchase in store are all revealing and actionable pieces of information. And if you don’t use them…someone else will. Customer expectations are exponentially increasing, so understanding how, where, and when they like to shop allows you to create a flawless shopping and service experience that invites five-star reviews, referrals, repeat purchases, and deep satisfaction. We tell all our clients that you should never collect data if you don’t intend to use it. If the touch points you’re collecting don’t correlate to customer action, we recommend you reassess the data you’re collecting. If you aren’t sure what KPIs to use, or how to find actionable customer insights, we can help.
Click here to explore how businesses like you have used this methodology and see how we can support your transition from outdated attribution models to high-performing, cross-channel tracking. And remember, you don’t need to take our word for it — Forrester agrees.Back to Thinking