Four Alternatives to Last-Click Attribution

Four Alternatives to Last-Click Attribution

Attribution Modeling

Advertisers have become accustomed to the belief that the final click that leads directly to the conversion is the most important click – hence the affinity for last-click attribution. But it’s important that businesses transition away from last-click attribution. That’s because last-click attribution fails to account for the value of the entire conversion path.

Most marketers would agree that their brand campaigns drive a large number of conversions and have very low costs per action (CPAs). Of course the cost per clicks (CPCs) in brand campaigns tend to be very low, but those campaigns are also benefiting from last-click attribution models.

Let’s think about a customer journey for a moment. With the holiday shopping season upon us, many of us will start our search for the perfect gifts with some online searching. Here’s how one of my searches might look:

Top electronic gifts 2018 -> Fitness Trackers -> Top Rated Fitness Trackers ->Apple Watch

In the example above, the brand campaign housing the keyword “Apple Watch” would get 100-percent of the conversion credit if you use the last-click model. Clearly, I did not start my search on a branded keyword, yet the brand campaign gets full credit. When marketers use last-click attribution, they generally see that non-brand keywords achieve low conversation rates and high CPAs, and brand keywords achieve high conversion rates and low CPAs. But is this approach really a fair way to evaluate our campaign and keyword performance?

Marketers have all seen non-brand keywords fail to work well in a campaign. They may be costly to run, and rarely do we see strong conversions. I have paused my fair share of non-brand keywords as I can’t justify their worth to my clients. Not surprisingly, I see search volume decline; and although my CPA often times improves, my overall number of conversions also begins to decline. What we have been missing is the ability to see the value of the entire conversion path.

Alternative Models

One of the main focuses for Google this year has been transitioning clients from last-click attribution into a model that gives credit to each paid click in the user journey. Currently, there several different attribution models available in Google Ads.

Let’s take a look at some of the choices:

Data-Driven Attribution

The model Google recommends most is data-driven attribution, which uses Google’s machine learning technology to determine how much credit to assign each click in the paid search journey. This attribution model is all based on an advertiser’s own data and continues to “learn” over time.

Data-driven attribution takes both converting and non-converting paths into account, and it’s powered by dynamic algorithms that assign credit to touch points based on fractional credit. Google recommends choosing data-driven attribution when available. Unfortunately, this attribution model is not always an option as it requires 15,000 clicks on Google search and 600 conversions over a 30-day period.  Although smaller advertisers will not have access to this attribution model, there are still some good options available.

Linear Model

The linear model distributes the credit for the conversion equally across all clicks on the conversion path. If it takes four clicks for a searcher to convert, each click receives an equal part of the total conversion credit.

Time Decay Model

The Time Decay Model gives more credit to clicks that happen closer in time to the actual conversion. For example, if the path to conversion takes five clicks, the time decay model would assign an increasing proportion of credit with each subsequent click, with the final click that led to the conversion receiving the most credit.

Position-Based Model

The Position Based Model gives 40 percent of the conversion credit to the first click, 40 percent to the last click in the conversion path, and the remaining 20 percent across the other clicks on the path.

A Recommended Approach

As mentioned above, if the data-driven attribution model is an option for your campaigns, always choose that. But if you don’t have enough data available for that option, how do you go about choosing among the other options? Google offers a few suggestions:

  • Choose a time decay model if your client has a conservative growth strategy, is a market leader, and has little competition. In this scenario, the final clicks in the conversion path will get more credit.
  • If your client is growth oriented, new to the market, and is facing a lot of competition, choose a position-based model where the first and last clicks in the conversion path will get the most credit while the clicks in between will receive a smaller portion.
  • If your client falls somewhere in between, you may opt for a linear model, giving equal credit to all the clicks on the conversion path.

There is no absolute right or wrong choice, and any of the models you choose will give you better insight into the complete conversion path more than the last-click model can. Google also offers an attribution modeling tool in Google Ads that allows you to change attribution models and compare results among the different model types.

Outcomes of Different Models

No matter what attribution model you choose, you should anticipate a decline in brand conversions and an increase in non-brand conversions. The actual number of conversions will remain the same regardless of the model you choose. But you will see fractional conversions reported, indicating each campaign/ad group/keyword that played a role on the conversion path.

So let’s revisit my holiday shopping search from above:

Top electronic gifts 2018 -> Fitness Trackers -> Top Rated Fitness Trackers -> Apple Watch

If I used a position-based attribution model, here would be the new breakdown for conversion credit:

  • 40 percent of the credit would be given to “top electronic gifts 2018.”
  • 10 percent of the credit would be given to “fitness trackers.”
  • 10 percent of the credit would be given to “top rated fitness trackers.”
  • 40 percent of the credit would be given to “Apple Watch.”

Using last-click attribution, I would see keywords “top electronic gifts 2018,” “fitness trackers,” and “top rated fitness trackers” appear to be poor performers, as all of the conversion credit would have gone to “Apple Watch.” Conversely, if I were to use the position-based model, I would see that all of those keywords together played a role in the conversion path — and I would have a better understanding of the value of my non-brand keywords. This insight would allow me to make smarter decisions when optimizing.

Without question, we are able to make smarter decisions when we have a better understanding of the full conversion path. I suggest taking some time to experiment with the various attribution models using the attribution modeling tool in Google Ads. Based on your findings, select the attribution model that best suits your goals. I have found the additional conversion path insight to be valuable.

For more insight into how to improve the performance of your online advertising, contact True Interactive. We’re here to help.

Photo by rawpixel on Unsplash

Five Options for Attribution Modeling With Analytics Engines

Analytics Attribution Modeling Spotlights

Man-outstretched-arms2Making adjustments. That’s the key to success, regardless of whether we’re talking about half-time adjustments in a big game or changes you make in your marketing plan. You have to observe, learn and adjust to what’s happening in your field of play.

That is what you will learn from our article “Five Options for Attribution Modeling With Analytics Engines,” a version of which initially was published on MarketingProfs (December 11, 2014), though its principles remain relevant today.

The objective of attribution modeling is to evaluate (by using analytics) what led to every sale—so we can replicate success.

In that post, we described five methods that command the most attention or offer the most promise.
MarketingProfs

  1. Last Click
  2. First Interaction
  3. Position-based
  4. Time-delay
  5. Linear

While “Last Click” used to be the only game in town, the rise of powerful – and often-times free – analytics tools like Google Analytics have greatly expanded the playbook for marketers.

Busy marketers often stick with what they’ve previously used. We get it. Learning and implementing a new model can take time. But the payoff is often worth the effort. For example, here are “3 Reasons to Drop Your ‘Last-Click’ Crutch.” When you’re ready to change your game plan, our previous post “4 Alternatives to Last-Click Attribution Modeling” also gives you guidance on choosing the model that’s best for you.

But never fear. Despite our admonishment to drop the “last-click” crutch, we let you know in “3 Tips for Managing Attribution Modeling” that it’s okay to use that crutch to prop up your analytics.

Today’s digital commerce is complex. In turn, smart marketing dictates that you make adjustments and invest your budget dollars where they will do the most good. We believe our tips will help point you in the direction of success.

Why Mom’s Advice Applies to Video Marketing

Analytics Attribution Modeling Video

Think of mom's advice when doing video marketingMoms love to toss out quips to keep their kids in line. Funny thing is many of them apply to marketers just as much as to children. (And let’s not read too much into that!) One Mom-ism you’ve probably heard is “It’s not that I don’t trust you, it’s that I don’t trust everyone else.”

She might as well have been talking about marketers who are hanging out with all the “cool kids” running video marketing campaigns. You shouldn’t blindly jump in just because they are. Do they know what they’re doing? And if their marketing spending is making a difference?

We previously looked at the explosive growth of video search. With video accounting for 64% of all Web traffic – and growing – clearly there is a huge opportunity. But opportunity alone isn’t reason enough to leap into video.

To be effective, at least at present, you need to be sure your attribution modeling is in place so you can judge the success of your paid video search. Start there, especially if your product or service is more of a considered purchase. You will drive more value throughout your campaign if you spend time upfront to understand your buyers and build models that help you know what’s driving their actions.

It’s also important to be patient with your campaigns. The downside of consumers viewing content when and how they want is it could take a while for your videos to be discovered and viewed by your target audience. Again, this is another good reason to ensure your attribution models are in order, so you won’t pull the plug too soon.

Once you have your attribution models set, should you immediately press the “on” button and recline with a bowl of popcorn and your favorite beverage? Maybe… maybe not.

To video or not to video

Essentially, there are three ways you can proceed:

  • Wait for the right time for you and your customers
  • Proceed slowly and cautiously, at a pace that avoids major gaffes
  • As quickly as possible; the Internet moves so fast, any mistakes will be behind you quickly

Which is the right way to go? Mom would say “I don’t know” is not an answer. And she’s right. Actually, any of them could be correct.

If you are an industrial or B2B marketer, and video isn’t prevalent in your industry, you can probably afford to wait. Particularly if you don’t currently have any video assets and your customers aren’t demanding that you get some.

If you are a retailer, or sell products or services through direct response, right now is a great time to get involved — especially if you already have some video available. The market is primed and the competition level is relatively low. You can “own” video search for much less than it might cost for text-based search. Even if you don’t have video right now, however, there are specialty companies that can help you develop some quickly – and at low cost.

If your organization is risk-averse, proceeding slowly might be the best bet. Try video on your website and gauge the reaction. Use your Google analytics to monitor how often your videos are viewed, if visitors are staying through them and if they are going from one to the next. That will tell you whether your content has the potential to work on a broader scale so you can expand into channels such as YouTube. (See my previous posts on quantifying the effectiveness of campaigns and using session metrics to learn more about insights you can gain from your analytics.) Even if you make a few missteps, the learning effort will be worth it, and those errors likely will be forgotten quickly.

Remember Mom

“Everyone else is doing it” wasn’t a good reason when you were a kid, and it’s not a good reason now. Having a solid business reason for launching a video search campaign – and the mechanisms to manage its effectiveness – will drive greater success in the short- and long-term. And make your mother proud.

Taking Measure of Paid Video Search

Analytics Attribution Modeling Video

chart bustingVideo is rapidly becoming the preferred method for consuming content on the Internet. From Netflix to Facebook to the video “granddaddy” YouTube, video already accounts for 64 percent of all Web traffic, and that figure is expected to rise to 80% by 2019. Video presents a wide range of opportunities for savvy marketers. But like anything else, you need to be sure you have a reason for getting into paid video search.

Just like mobile marketing, you still need to get people to find your videos, then measure the effectiveness of each click. Tools are being introduced that make it easier to measure the effectiveness of paid video search. For example, Google is making a real effort to integrate the YouTube advertising platform into AdWords. They also have a product in beta called TrueView for Shopping that combines video with shopping feeds. Consumers can watch a video, click on a product image and shop right there.

That should help overcome one of the biggest objections, which is the lack of ability to directly attribute a purchase to a consumer watching a video. Currently, Google recommends using attribution modeling to measure the effectiveness of a video. With TrueView for Shopping, however, marketers will be able to use last-click conversion measurements much more effectively. Finally, you will be able to see hard data on which videos work and which fall flat. Do you need more explainer videos, or does your audience prefer humor? Is 30 seconds the ideal length, or are your prospects seeking long-form content?

Change in the way video is consumed

Perhaps one of the biggest factors contributing to the growth of video is the change in the way it’s consumed. Video viewing (think television) used to be controlled by the content providers.

Now anyone can watch what they want, when they want. YouTube, Netflix, Hulu and their ilk have seen to that. Measuring the audience has been challenging, although Nielsen may have cracked the code on Netflix. On other sites, Google TrueView will ensure you’re paying only for actual views, rather than estimated viewership.

The net takeaway is consumers are not spending as much time flopping on their couch watching whatever is pushed to them. Instead, they are seeking out content on their own terms, and on a variety of devices. YouTube claims that advertisers have seen click-through rates for these more targeted ad videos that are 3-4 times higher than other video ad formats.

There’s always a “but…”

With all that going for it, why shouldn’t marketers just jump whole-hog into video? To be effective, at least at present, you need to be sure your attribution modeling is in place so you can judge the success of your paid video search. If it isn’t, you need to get that house in order first. Especially if your product or service is more of a considered purchase. Taking time to understand your audience and build the models will help you drive more value throughout your campaign.

Having a deeper understanding into which video ads work is, of course, a tremendous boon for marketers using that medium. But before you get to the point of placing video ads, you must produce the actual videos. While that doesn’t have to bust your budget, it isn’t always cheap. Are video ads right for your marketing plan?

As I said in my previous post, this is the time to recall the wise words of your mother: “If your friends were jumping off the roof, would you do it too?” Just like back in those days, you need to carefully consider the risks and measure them against the thrill of the leap. In my next post, I will give you some pointers to help you make that determination – “To video, or not to video?”

When It Comes to Paid Video Search, Listen to Mom

Analytics Attribution Modeling Video

In Video Search - Listen to your mom's adviceBy now you’ve probably heard the declaration that 2015 is the “year of video marketing.” The pundits declared it, the headlines have screamed and the actual numbers are certainly making a good case for it. Of course, all this talk is making marketers nervous as they fear they’re being left behind.

That’s why in times like these it’s important to remember the wise words of your mother.

Nearly all of us at one time or another begged to be allowed to do something or see something or go somewhere because all the other kids were doing it. And what was the universal response of all mothers everywhere? “If your friends were jumping off the roof, would you do it too?”

Yes, video is growing and presents a wide range of opportunities for savvy marketers. But like anything else, you still need to be sure you have a reason for getting into paid video search. Here’s a look at what’s driving the trend, as well as the factors that will help you decide whether it makes sense for your organization, and provide some ideas on what to do if it does.

Explosive growth

There is no dispute that video is rapidly overtaking text and images as the preferred method for consuming content on the Internet. Video already accounts for 64 percent of all Web traffic, and that figure is expected to rise to 80 percent by 2019.

Part of the reason for this growth is the continued use of mobile to watch video. For example, YouTube says half of all views of its content are on mobile devices. As more videos become mobile-friendly, and wireless connections get faster, you can expect that figure to continue to rise.

But it’s not just about greater availability. Forrester estimates that one minute of video is worth 1.8 million words of text as far as the message communicated. That’s pretty attractive to marketers in their ever-present quest to break through the clutter.

The big attraction of video to marketers, though, is that it is currently the road less traveled. Traditional paid search has become ultra-competitive (and expensive), in part as a result of developments such as close variant matching (CVM). As search results are broadened to the “close enough” level, more marketers are jumping in. Since fewer organizations are taking advantage of video search, eyeballs can be acquired for a relative bargain. Mom would appreciate that thriftiness.

While these numbers may make your eyes bulge, remember – it’s not as simple as posting a clever cat video to attract your audience. (Though cat videos, inexplicably, always seem to do well.) Just like with mobile marketing, you still need to get people to your videos, then measure the effectiveness of each one. If you know the tools to use – and how to use them – you can track the path from a video view all the way through to a purchase.

In my next post, we will look at some of those tools and how savvy marketers are using them for last-click conversion measurements. This is one instance where Mom would encourage you to do what the other kids are doing.

3 Tips for Managing Attribution Modeling

Analytics Attribution Modeling

For months, our rallying cry has been “Drop your Last-Click Crutch!

Our argument is straightforward: How can marketers track the digital pathway buyers followed to reach them if the only clue is the buyers’ final step?

Sure, not long ago, we had little choice but to rely on the last click. The data connecting each touch point along a customer’s path to purchase wasn’t available or reliable. What’s more is the tools for analyzing this type of information were neither sophisticated nor affordable.

And yes, time was spending most of your marketing time and budget figuring out whether or not marketing was working just didn’t make a lot of sense. What did make sense was giving the last marketing tactic in a campaign that produced a sale 100% of the credit, because the data was fresh and unambiguous. We knew it was real — even though we also knew a mix of campaigns and as many as five touch points preceded that sale. In those days, we just couldn’t see those facts in front of us.

Well, today we can. Google’s recent research tells us as many as nine of every 10 marketers has access to some form of analytics tool, and the reasons for using those tools are more compelling than ever:

  • 90 percent of media interactions today are screen-based, a statistic that includes TVs, PCs, smartphones and tablets
  • 67 percent of buyers start shopping on one device and continue on another.

In other words, today’s digital commerce is complex. In turn, Smart marketing dictates that you invest your budget dollars where they will do the most good. And in my last post, we offered four ways you can approach this analysis – i.e., we’re pointing directions for stepping beyond the last click.

We understand that throwing down that last-click crutch and venturing into new analytical terrain can be intimidating, especially without a trusted means of support. So, here are a few pointers for approaching attribution modeling with new techniques:

  1. Know Before You Go. Earlier, we referred to the way today’s customers come to your company as a digital pathway. So, let’s stick to the analogy. If you want to discover a route to a new destination, you look at a map. In the case of attribution modeling, you should plug data into your analytics tool – just like you enter addresses into mapping software before hitting the road. Be sure full details – tactics, dates, dollars, etc. — about each digital campaign are entered into your modeling software.
  2. Walk First, Don’t Run. Explore alternative attribution models one at a time before trying combined or comprehensive analysis with any given technique. Before attempting an obstacle course, walking along the path and examining each challenge is a great way to prepare and minimize stumbling when the time comes to run the race.
  3. Carry Your “Last-Click Crutch.” Ok, we confess we were going for dramatic impact when we told you to “drop” your crutch. But that doesn’t mean we believe you should disregard it. Last-click analysis plays an important role in attribution modeling. Your picture of your customers’ journey would be incomplete without being able to see their final steps. So, you shouldn’t lean on that crutch, but you should carry the knowledge of how to use it along your way.

Expect some confusion at first but your competency will grow with time. And after a few trips, you’ll be finding efficient shortcuts and some more scenic routes than you’ve traveled before.

4 Alternatives to Last-Click Attribution Modeling

Analytics Attribution Modeling

My last post framed today’s marketing challenge as investing budget dollars where those funds will do the most good – and doing it quickly and precisely.

And then, I posed this provocative question: How can you meet that challenge without practicing sophisticated attribution modeling?

By sophisticated, of course, I mean dropping your Last-Click Crutch and using the powerful attribution analytics available to you to dig deeper. Here are four attribution modeling methods worth exploring for your digital campaigns:

1.  First Interaction. In this model, you’re placing all your focus on discovering what caused a prospect to become interested in your products or services in the first place. Did they click on a banner ad? Search on specific keywords? However they got there, this view can be just as limiting as Last Click, if you apply it in isolation. You still would have only one touchpoint on which to base your marketing decisions – it’s just moved to an earlier point in the process.

2.  Position-Based. Now we’re getting somewhere. With this model you’re accounting for all the different positions in the sales funnel and weighing them based on what you believe to be most important. For example, you may give 40 percent of the weight to First Interaction, 40 percent to Last Click, and 20 percent to what happens in the middle. The key is it’s showing every single touchpoint throughout the sales cycle. As you learn more about what motivates your customers to action, you can adjust weighting to better reflect how they interact with your brand. You can set up multiple customer models to give weight to different touchpoints, too. You also can perform a great deal of customization based on what’s important to the sale. For example, you can make adjustments for time on your site, page views (the more pages viewed, the more credit a particular channel gets), position rules that weight the value of a conversion based on each interaction, and more.

3.  Time-Delay. As the name implies, while you’re still looking at the entire sales funnel you give more weight to actions that occur closer to the conversion. So, for example, while some credit is given to an organic search that occurred 30 days ago, it is not nearly as much credit as the banner ad that was clicked two days ago, or the paid social media ad that was clicked today.

 4.  Linear. This model is incredibly powerful, but also requires the greatest degree of expertise. Rather than working from a starting point, you are customizing everything, with many more parameters available to you. Really, it’s the best of all the other models, combining elements of Positioned-Based and Time-Delay. For example, you can look at media in the past and the actual media type. If you feel paid search is more important than organic search, you can adjust the weighting that way. You can look at the path to get to a conversion and/or you can look at the different interactions.

All this capability at your fingertips can be confusing at first. Your best approach is start slowly with one of the less complicated models, and as your competency grows move into Linear attribution marketing. The process will take time. Be patient, and tweak, tweak, tweak as you learn.