When you work in marketing, you believe in marketing.
Maybe you and your team have done all the research, been careful to stay on top of the marketing trends of the day, made investments in the technology, and pursued all the marketing channels that promised to provide the biggest payoff. Maybe you’ve done everything you know you’re supposed to be doing. But feeling confident that your work is paying off isn’t going to be enough to get the budget approved each year. You need to know.
No matter who’s asking, the results come out the same: figuring out ROI is one of the biggest struggles facing the marketing industry today. This article examines this challenge and presents solutions for helping you overcome the obstacles.
Why determining marketing roi is difficult
Using the data you have to get a complete view
The problem of proper attribution
Embrace a data-driven approach
Everyone knows you have to spend money to make money. That’s why digital marketing alone is a nearly $62 billion industry and many of the most successful companies in the country devote a significant percentage of their budget to sales and marketing activities.
The ongoing quest to bring in new customers is a huge part of doing business successfully. With businesses across the board sinking significant investments into hiring marketing talent and purchasing marketing technology – a field that doubled in size from 2014 to 2015–the obvious question that executives face at the end of the day is: does it all pay off?
Do you know the answer?
When you work in marketing, you believe in marketing. Maybe you and your team have done all the research, been careful to stay on top of the marketing trends of the day, made investments in the technology, and pursued all the marketing channels that promised to provide the biggest payoff. Maybe you’ve done everything you know you’re supposed to be doing. But feeling confident that your work is paying off isn’t going to be enough to get the budget approved each year. You need to know.
Survey after survey has found that marketers struggle with showing ROI. HubSpot found it to be the #1 challenge marketers face. 68% of marketing professionals told Adobe that they feel pressured to show more of a return-on-investment for their efforts. 60% of social marketers surveyed by Simply Measured ranked it as their top challenge, edging out all other options on the list.
No matter who’s asking, the results come out the same: figuring out ROI is one of the biggest struggles facing the marketing industry today.
68% of marketers … feel pressured to show more of a return-on-investment for their efforts.
Why determining marketing roi is difficult
The industry is filled with marketing products designed to collect marketing data. Talk of marketing data and measurement seems to be on everyone in the industry’s lips. Most marketing professionals aren’t dealing with a lack of data. The data’s there. So why is ROI still so elusive?
Many Marketing Goals Are Difficult to Measure
Every sales team has a clear and easy-to-measure goal: get more sales. For marketers, that’s the ultimate goal, but it’s just one on a list that includes much more subjective and difficult to gauge items like brand awareness, engagement and authority.
While less tangible than a sale, marketers have figured out a good number of key performance indicators (KPIs) that can help measure how well their marketing campaigns are pulling these goals off. A growth in website traffic or brand mentions around the web suggests you’re achieving more brand awareness; an uptick in email subscribers, blog comments, and social shares can all point to increased engagement; and when other experts and brands in your space link back to your site or content, that’s a sign of authority.
Nonetheless, it’s hard to know how well the KPIs really represent the goal at hand. And it’s even harder to figure out how they contribute to the larger, ultimate goal of increasing sales.
Most Marketing Metrics Only Tell Part of the Story
At this point, pretty much every marketing organization has a wealth of marketing data in various silos. But that data can only show you one part of the bigger picture.
Your cost-per-click metrics can tell you something about how well your pay-per-click efforts are performing, just as the number of downloads for a piece of content can show you how many leads it’s generating. But if those metrics remain in isolation – stuck in different dashboards or spreadsheets that are only viewed separately – then you’ll never be able to see any correlations or how they contribute to eventual sales.
49% of marketers have admitted to only collecting basic metrics, like clicks, views, and downloads.
Even recognizing this, many businesses stop at seeing a few disconnected slivers of the larger story. 49% of marketers have admitted to only collecting basic metrics, like clicks, views, and downloads. Why should you be content to read one chapter of a book, instead of following the full narrative?
Lots of Equations for Marketing ROI Exist, But Few Seem Comprehensive
If you’ve ever pondered the question of marketing ROI and turned to the resource we all use for answering our questions these days, Google, then you’ve encountered a large number recommended equations and calculators that promise to determine marketing ROI, many of them even claiming to be “simple” or “definitive.”
If they delivered on their promises, then the problem would be solved and marketers would have nothing more to worry about. In fact, finding marketing ROI is not simple. Getting to a place where you can apply some accuracy to the process takes time, skill, a lot of data, and sophisticated technology. An equation you find online might help you find a measure of your ROI for one part of your marketing, but no one equation will provide a comprehensive view.
Using the data you have to get a complete view
The good news is that you’ve probably already completed the first step in performing revenue attribution. Many of the marketing analytics you already have are an important part of the process, but as long as they’re stuck in a lot of disconnected spreadsheets or the dashboards of a number of different tools, you’ll won’t be able to make the connections you need to between them.
The next step is letting a central marketing performance management platform pull the relevant data together from the different silos. Once you can see all the metrics from your different teams and departments in one place, you can start to connect the dots and see how everything relates.
When all your data is viewable in one tool with a powerful marketing dashboard, you’ll be able to see the information in all new ways that bring about useful insights, including:
- Bringing data from social media, sentiment analysis, and customer survey sources together with data from demand generation, branding, and awareness campaigns
- Being able to compare results from various marketing channels to see correlations and dependencies
- Filtering your dashboard view based on the groupings of information most valuable to you, such as buyer’s journey stage, persona, or specific product or business segment
Most importantly, you can begin to make connections between your general marketing analytics and the specific leads and opportunities interacting with your marketing channels. Now that technology makes it possible to recognize repeat visitors and connect the user behind a click to their other online actions, you can follow the series of touch points of each lead as they make their way through the buyer’s journey. Since the marketing performance management software can also pull cost and revenue data from your CRM or budget files, you can then connect all those touch points to the eventual sale they contribute to.
There are a lot of steps to get more accurate revenue attribution, but many businesses are starting to make the move beyond just collecting metrics to connecting all right the dots that show how those metrics relate to revenue.
The problem of proper attribution
If you’ve started to analyze your marketing performance in terms of revenue attribution, you’re already ahead of many marketers. A recent study from Demand Metric and VisionEdge found that nearly half of all marketers focus merely on producing campaigns, without making use of any data to improve them. Only 21% have actually shifted their focus to providing tangible value to their companies using data-driven marketing.
Even so, there’s more to do and learn within the realm of revenue attribution itself. You see, tracking the steps in a particular buyer’s journey tells you what each lead encountered on the way to becoming a sale, but doesn’t really tell you which marketing touch points made the most difference in getting them to the point of buying.
Trying to figure out where the main credit lies is tricky. Did the product demo play a bigger role in that sale than the educational blog post the lead viewed? What if the blog post was the first thing that brought them to your site to begin with? You could make some guesses and assumptions about which marketing activities are making the biggest difference, but information based on assumptions is never ideal.
Here are several attribution models to determine how to divide credit between all the touch points in a buyer’s journey.
The first-touch attribution model tends to be the default mode for marketing organizations that haven’t yet dipped their toes into trying more sophisticated modes of revenue attribution. It’s the go-to model because it’s easy and seems pretty straightforward: you give credit to the first interaction a new lead has with your brand. The metric that captures whatever seems to be the first thing that brings them your way is given the full share of credit for the eventual sale.
This model provides a lot of credit to marketing activities devoted to raising awareness of a brand, like Google Adwords and SEO, and no credit to the steps that typically exist between when a visitors comes to your site for the first time and when they become a customer. Things like downloading a whitepaper, signing up for the email list, registering for a demo, or interacting with a sales rep get overlooked entirely, even though most marketers feel they play at least as important of a role in driving sales as that first touch.
Nearly half of all marketers focus merely on producing campaigns, without making use of any data to improve them.
Last-touch attribution is also pretty simple and straightforward, like first-touch attribution; it simply shifts the attention down to the other end of the buyer’s journey. Under this model, all credit for the sale is awarded to the last marketing activity of a prospect before they’re moved into the sales pipeline. In most cases, this means awarding some those marketing activities that first-touch attribution ignores, like signing up for a demo or responding to a contact CTA in an email.
Last-touch attribution makes a certain amount of intuitive sense. That last touch point is the one that really seals your prospect as a solid opportunity – it’s the thing that drives them over the second-most important line in the whole process (the last one being the sale itself). But it still means ignoring a lot of the other steps a lead takes before they get to that point.
Evenly Weighted Attribution
Here is a revenue attribution model that takes all of the steps of the buyer’s journey into account. Evenly weighted attribution is the most straightforward of the multi-touch attribution models. Quite simply, you divide the revenue for the sale between all the touch points equally.
This will usually provide a more accurate picture than either of the single-point attribution models since it takes the bigger picture into account and doesn’t ignore any of the marketing activities that played a role. Of course, if it were a perfect model for revenue attribution, our list would end here.
The problem is that all of the marketing activities a lead interacts with aren’t equal. We know that intuitively. The third blog post they read on the website probably doesn’t play quite as big a role in their ultimate decision to buy as their first visit to the website or the webinar they attended later. We can feel that some touch points matter more than others, but figuring out just how to measure that is tricky.
Time Decay Attribution
The idea behind time decay attribution is that chronologically, as a lead moves closer to the point of sale, their marketing interactions become increasingly valuable. Every touch point is counted, but each concurrent marketing activity gets a little more credit than the one that came before, with the final touch point being awarded the most.
This multi-touch model is appealing if you believe that the later stages of the buyer’s journey are more important and persuasive than the earlier, more awareness-based ones. While in some cases, those later touch points may be doing the most heavy lifting to get your prospects to the conversion point, in saturated industries those touch points don’t matter at all if your earlier awareness-based marketing activities don’t do the very important work of alerting the lead to your existence to begin with.
This is time decay attribution’s biggest weakness: it (arguably) undervalues the importance of the broader, top-of-the-funnel work that makes up a big part of what marketing does.
Position-based attribution combines the thinking of our earlier single-touch models with a multi-touch attribution approach. The first and last touch points got credit in those early models for a reason – they’re clearly two of the most important steps in the process. As such, position-based attribution gives the first and last touch points the most credit and then divides the rest equally between all the other touch points.
This model’s a bit more sophisticated than many of those already listed, but still flawed. Chances are, the other touch points don’t all hold precisely equal weight in terms of their importance to the sale. And the first and last touch points are both clearly important, but it wouldn’t be hard to find someone on your marketing team that can persuasively argue that they’re not that much more important than the other interactions your prospect has with your marketing materials.
W-shaped attribution still gives the first and last touch points special places of honor in the model, but adds one more touch point to the “most important” list: the one where your contact turns into a lead. In this model, each of these three touch points that are deemed the most important are provided the most credit, with the rest divided evenly between all the other touch points.
This model naturally brings up the question of just how you define a lead. Is it the first time your contact hands over their email address? Or is it when they specifically take the step of signing up for a product demo?
That fuzziness on how to clearly define the point where a contact converts into a lead complicates this model. Everyone has to be on the same page on what action should be counted as the middle of the W, or you’ll end up with dissension in your ranks. This model also has the same flaw we’ve come back to time and again, did these three touch points really play a more significant role than the others? Are all the other touch points really equal in value?
While each of these models manages to get a little more sophisticated in how it looks at the value of different marketing activities, ultimately they all involve a lot of guesswork and assumptions about what your prospects are thinking.
Here’s the model where marketing intuition comes more into play. You and your team probably have some strong opinions on which marketing activities are the most important to the process. Interaction-based attribution models allow marketing professionals to weigh in and decide which specific activities should be given more weight.
In most cases that means that activities that require more interaction or commitment from prospects get the biggest share of the credit. Passively reading a blog post or watching a video would count less than downloading a whitepaper, which would in turn count less than attending a webinar. Each of these activities requires a different level of interaction and investment, a blog post might take up 10 minutes of your day, but a webinar involves not only giving the company some contact details, but also showing up at a set, scheduled time for a presentation.
This one is hard to get right, because it depends so much on subjective opinions. Marketing professionals can be extremely knowledgeable and experienced and still have some assumptions about their work that turns out to be wrong.
The problem with all these rules-based attribution models really all comes back to the same thing: we can’t read the minds of our prospects. None of the information we have access to tells us what they’re thinking as they go through the steps that lead them to the point of sale. Skilled marketers can make some good guesses at which touch points are playing the biggest role, but at the end of the day they’re still guesses.
Statistically Inferred Revenue Attribution
Marketers who embrace a statistically inferred revenue model are on the path to the most accurate form of revenue attribution possible. This advanced model uses past touch point data to better gauge how much credit should be given to different types of marketing activities based on their effect on closed won deals over time. That way, if the act of downloading a whitepaper frequently precedes a sale, the model gives that touch point more credit. If blog posts covering a particular topic have a high rate of attracting leads to the website who become customers, the revenue model takes that into account. You know to give them more credit.
The challenge with statistically inferred revenue attribution is that it’s not quick and easy – you can’t start doing it from scratch. It takes some time to get to the point where you have enough data to effectively determine what’s working and how much credit should be allotted where.
Until recently, this level of accuracy in revenue attribution was something marketers could only dream of. But it’s just one more part of the marketing landscape that’s been completely reshaped by the advent of new technology tools. Getting it right still requires time and work, but the possibility is finally within reach.
Embrace a data-driven approach
Few things in marketing are fast and easy, and when you accept the need to play the long game it often pays off. A shift to data-driven revenue attribution, which inevitably precedes a larger shift toward data-driven marketing, pays off on two especially important levels:
- You’ll have the answer to marketing’s biggest problem: you can finally show clearly the ROI of your marketing activities.
- You’ll start to see which of your efforts are working, which gives you the ammo you need to refine your marketing plan for greater success, as well as predict marketing impact on revenue.
Many marketing departments find it easier to keep doing what they’re doing, focusing on activity rather than impact, but savvy marketing teams are starting to see that there’s a better way. The sooner you join the 21% of marketers using data-driven marketing to create proven value for their organizations, the better a chance you have of staying competitive in an increasingly complex marketing space.