Keeping a close eye on the data produced by your AdWords e-Commerce campaigns is absolutely critical. Without proper measurements, how will you know if you’ve spent your advertising budget effectively? Any company doing advertising on AdWords should be optimizing individual ads and the keywords within them.
Each keyword should be evaluated to ensure that they are generating a positive return and helping your company to achieve its overall business goals. But in a digital landscape where we are interacting with customers through multiple channels, figuring out how to credit each conversion can be difficult. Attribution mistakes lead to misleading results.
For e-Commerce companies with many products, sifting through your AdWords account can be difficult. Many companies find themselves only analyzing overall profitability and under-analyzing individual ads. This leads to a lot of wasted advertising spend and money left on the table. Having a deep understanding of how ads within specific areas of your funnel are performing is important for long-term success. Without knowing this, it is nearly impossible to properly allocate your advertising budget.
Fortunately, Adwords includes tools that help companies analyze the effectiveness of each channel. The most prominent of these tools is conversion attribution. Conversion attribution deals with assigning credit from conversions to components of your marketing funnel. The models included in this system include last click, first click, linear, time decay, position-based, and data-driven attribution. Of course, none of these attribution models are perfect. Each option has its own pros and cons and the model that your company chooses will depend upon your business goals and the products that you are selling.
Let’s take a deeper look into each attribution model:
Last Click Attribution
Last click attribution is a popular, straight-forward attribution model. It assigns 100% of the credit for each conversion to the last ad that the user clicked and the keyword that was searched to trigger the ad to display. Last click attribution is easily the most popular method of attribution because it is easy to understand and use. But that doesn’t mean that is always the best choice for e-Commerce businesses.
Attributing all conversions to the last ad that was clicked undervalues other marketing materials that the user came into contact with before converting. Few e-Commerce brands lack a multi-channel digital strategy. Those mid-funnel marketing materials play an important role in educating and nurturing customers. Most customers go through a research and nurturing process before making the choice to buy a product and overlooking their usefulness in your funnel can lead businesses to focus on the wrong areas of their advertising strategy.
Some customers require a longer nurturing process than others. You’d be hard-pressed to find customers that weren’t influenced by marketing materials outside of the last ad that they clicked on in one way or another. That’s why it’s important to track the effectiveness of all marketing channels, and last click attribution is not a great solution in that regard. Last click attribution can completely skew the data used in the ad optimization process. This leaves money on the table and continues to ensure that your advertising dollars are not spent effectively.
That doesn’t mean that last click attribution is useless, though. There are definitely situations where it is a clear choice. It is typically the best fit for businesses that are selling inexpensive items that don’t usually necessitate research before buying.
First Click Attribution
First click attribution is the opposite of last click attribution in that the conversion credit is assigned to the first ad and keyword that clicked. Like last click attribution, this model has some serious flaws in representing the customer journey, particularly as it applies to e-Commerce companies. It’s easy to see why this attribution model would devalue other important marketing materials on the customer’s path to purchase.
Big ticket items could benefit from using first click attribution because the ad that is credited began the nurturing process for consumers. First exposure to your product eventually led to a sale so that initial ad deserves some credit. Branded campaigns are the bread and butter of many eCommerce business so it is important to know where and how consumers are being introduced to your products. It’s also imperative, and possibly more so, to know what keywords are closing your sales which is a major flaw in using this type of attribution model.
In linear attribution, each individual step along the customer’s path to conversion receives equal credit for the conversion. It’s the most simplistic of the multi-touch attribution models. There are a lot of benefits to this model, namely that marketing channels throughout all stages of your sales funnel receive credit.
This provides a more complete picture of your allocated advertising dollars but does have its own issues. For e-Commerce companies, linear attribution can serve as an excellent starting point for sharing credit across marketing channels, especially when you don’t have the traffic necessary to qualify for Google’s data-driven attribution feature.
The one downside to linear attribution is the fact that it doesn’t account for the varying impact of each individual channel. While a prospect might interact with several advertising channels, it stands to reason that a specific channel would play a larger role than others in their decision to purchase. How would you know if a post on your company blog played a huge role in influencing their decision to purchase? You wouldn’t, and missing that fact may lead you to draw the wrong conclusions. It’s difficult to know where to begin account optimizations when every campaign is being credited equally.
Time Decay Attribution
In time decay attribution models, the most recent touchpoint of the conversion path receives the most credit, while earlier interactions receive less credit on a sliding-scale. The longer the time period since the customer interacted with a channel, the less credit it receives. This model makes the assumption that the closer the customer gets to the conversion, the more impact the marketing materials will have.
Related: How Quality Score Affects Your Ads
This presents a problem because it naturally gives less credit to the top-of-funnel marketing channels. These channels are always the farthest from the conversion and therefore are undervalued by this model. Additionally, it provides even less credit to top-of-funnel marketing channels when the customer engages in a long research and nurturing process. The top-of-funnel channels will receive more credit from customers that conduct faster or more precise research. This model is appropriate for low-dollar items that don’t require a lot of research before buying.
Position-based attribution (also known as the U-Shaped attribution model) gives the first and last clicks 40% of the total credit each while spreading the final 20% evenly among the other touch points throughout the customer journey. Typically, position-based attribution is an excellent method for marketing teams that are focused on lead generation. There, the first and last touch are more likely to outweigh mid-funnel touches in terms of importance.
It is used less in e-Commerce advertising, but there are still some interesting ways that it can be used to gauge effectiveness at both ends of your funnel. This model favors the first and last touch because they are the points where the customer begins to interact with your company and the last touch that leads to conversion.
The position-based attribution model has some downsides for e-Commerce businesses. It provides heavy-handed credit to the first and last touch, but very little credit to the touch points between. Position-based attribution is most often employed for high-dollar products that necessitate a sales call before conversion.
Data makes the world of search keep turning, and Google has been making a strong push for more businesses to use their data-driven attribution model. The data-driven attribution model uses click data from your account to assign conversion credit. The system assigns credit to specific ads, keywords, and campaigns that — according to the data — have played the largest roles in driving the sale.
Data-driven attribution compares the paths that customers took, comparing converting customers and non-converting customers to one another to find which channels are typically the most influential in the sales process. Once the system identifies a pattern, it assigns weighted credit to multiple channels. For e-Commerce companies, data-driven attribution is often the best choice. Not only does it ensure that every channel a user interacts with is accounted for, but it provides a data-based approach to weighing the effectiveness of each channel.
There are some things that need to be taken into account if you plan on using data-driven attribution. The biggest hurdle is the fact that there are a number of thresholds that need to be met in order for the model to have enough data to provide effective conclusions. To enable data-driven attribution, an account must have at least 15,000 clicks and 600 conversions within a 30-day period. To reach this threshold, AdWords always looks at the previous 30 days, which means that you must continually stay above this mark. Smaller companies may find that data-driven attribution just isn’t an option for them.
Choosing an attribution model is a very important decision for any company. It has a drastic affect on the allocation of your advertising dollars and return on your advertising spend. The attribution model that you choose should be decided once all of your business goals and objectives have been clearly defined.
No model is perfect, and what is a great choice for one company is not necessarily a good choice for another. Each has its own advantages and disadvantages, and none provides perfect analysis of your overall advertising efforts. Ultimately, the model that you choose will be the basis of all ad campaign optimizations that you make. It is crucial that you take the time to fully understand the different attribution models to find the one that best suits your marketing and sales processes.