7 Steps to Multitouch Attribution Management

Journey-Driven Consulting

Analyzing a Buyer's Journey

Today’s digital advertisers know that first and last-touch attribution analysis paints an incomplete picture of the customer journey. Once potential buyers express initial interest, they make a set of interim decisions along the purchase path -- informed by paid search, display ads, social network interactions and a range of other on and offline influencers.

MTA, or multi-touch attribution, enables the marketer to construct a holistic story — one that describes and calculates overall campaign effectiveness — by drawing on an analysis of how various paid touchpoints interact to influence and convert the buyer.

In this piece from Razorfish, we highlight how marketing and advertising executives, who are eager to adopt multi-touch attribution, can implement a successful onboarding process to pave the way for a smooth implementation by:

  • Evaluating an in-house solution vs. multi-touch attribution vendor
  • Selecting the right attribution vendor
  • Implementing an attribution vendor solution
  • Evaluating initial attribution results
  • Implementing a crawl, walk, and run approach to optimization 
  • Measuring
  • Setting expectations

The trend

In recent years, an increasing number of marketing and advertising executives have adopted MTA as a primary means to measure campaign effectiveness. Executives also depend on MTA to make more informed budget allocation decisions. 

While executives are sold on MTA’s benefits, they struggle with its actual implementation. 

In the great majority of cases, MTA success is directly dependent on a sound onboarding and implementation process. MTA success is also dependent upon a complete setting of expectations that will prepare executives for the requisite decisions needed to ensure a smooth implementation.

Times Square at night.

1. Evaluating an In-House Solution vs. Multi-Touch Attribution Vendor

Many marketing and advertising executives struggle with evaluating the pros and cons of engaging a third-party attribution vendor versus building an in-house solution. Consider these trade-offs when making the decision:

Cost

  • Executives with relatively small advertising budgets will benefit from hiring a lean team (~2 FTEs) to build out an in-house attribution model. 
  • A third-party vendor requires an annual or quarterly contract, which ranges from $20K to $60K per month, depending on the number of channels, impression/click volume, and add-on capabilities. 

Data processing/integration​

  • Compared to an in-house solution, third-party vendors may have a more robust data infrastructure, which can process billions of impression/click data per month in a relatively short amount of time. 
  • A faster data processing time allows businesses to use close to real-time attribution results and make better campaign optimizations.

UI/reporting capabilities

  • Third-party vendors usually offer a more sophisticated UI, data visualization, and reporting capabilities, where users will be able to export raw data for customized analyses.

Customization of the model

  • In-house solutions may be able to accommodate more tailored data solutions to better align with business objectives. However, increased complexity may require additional people and/or skills. 

Industry experience and resources

  • Vendors may have more experience with attribution modeling across various industries. And they are usually the first to adapt to the latest advancements and emerging trends in attribution.

 

2. Selecting the Right Attribution Vendor

Assuming a third-party partnership is your preferred choice, what’s next? Establishing a scorecard  is often a good way to rank your short list of attribution vendors based on the attributes (listed below) that are most important for the business. The “Forrester Wave™: Cross-Channel Attribution Providers” is a helpful resource for attribution vendor evaluation. It provides a detailed analysis and review of the top attribution vendors in the market and includes many of the criteria that are included in this list. 

Top vendor evaluation criteria

Cost/tech stack

Monthly cost varies depending on the vendor, impression/click volume, and number of tracked channels. Larger technology companies, for example, may also offer special pricing for their existing clients who choose to use their multitouch attribution solutions.

Industry experience

Traditional vendors often have more experience in the industry, but newer attribution vendors may have better data-streaming capabilities, methodologies, or customer service that often trumps their lack of years of experience. 

Model methodology

Every attribution vendor uses a different methodology to measure the effectiveness of individual touchpoints. These include A/B lift comparison, survival analysis, game theory attribution, discriminant analysis, or a combination thereof. It is important to select the methodology that best aligns with your business model. Keep in mind: data refresh/processing speeds are also dependent on the complexity of the model. 

Tracking/data collection

Depending on the vendor, data can be ingested through either cookie-log files or a tag-based-only approach. 

Reporting cadence/UI capabilities

Data refresh cadence may range from daily to monthly, which can affect the organization’s ability to make up-to-date optimizations. Vendors with sophisticated UIs will be able to provide other helpful campaign insights, such as cookie reach, overlap, frequency, time lag to conversion, and conversion path. 

Third-party integration 

Many vendors will allow MTA data to feed into DSPs or search management platforms for real-time optimization. Some vendors can also integrate with cross-screen technology providers, which will result in a more holistic view of a customer’s online journey. Some MTA vendors may also provide cross-device insights via third-party integration with BlueCava, Tapad, etc. 

Above-the-Line/offline capabilities

Some vendors may use multiple models — such as media mix modeling in conjunction with attribution modeling — to account for TV or above-the-line “ATL” activities. It is also important to study the vendor’s capability in reporting on multiple KPIs, especially as upper-funnel campaigns will likely have different KPIs than acquisition campaigns. 

Customer service

A good service team should respond to ongoing technology and analytics needs while providing extensive support in the initial implementation process.  

3. Implementing an Attribution Vendor Solution

Once the attribution vendor or attribution methodology has been selected, it is crucial to cover all the necessary steps in the onboarding process to ensure a smooth transition.

1. Define business goals and KPIs

  • Establish key performance indicators (KPIs), secondary metrics, and success factors based on business objectives. 
  • Determine look-back window. Potentially start with a longer time frame and slowly adjust after analyzing average time lag to conversion.

2. Identify tracked channels

  • Channels with proper tracking already in place should be onboarded first to minimize implementation error.
  • Whenever a new channel is added to MTA, credit allocation may change across existing tracked channels due to potential cross-channel interaction.

3. Define tracking logic and data ingestion

  • Document how each channel is tracked and categorized (cookie data pass-back or tag-based solution).
  • Establish data integration plan (e.g., how MTA platform will obtain costs and cookie-level data from ad servers, publishers, and other sources).

4. Establish a detailed QA process

  • Make sure that a detailed QA process is in place to check for impressions, clicks, and action counts that are being tracked. For tag-based solutions, a daily action tracker is recommended to check for consistent activity. 

 

4. Evaluating Initial Attribution Results

Once attribution results are made available, thoroughly review the data and check:

  1. That activities captured in MTA match the data from the ad server (impressions, clicks, cookie reach, etc.). Any discrepancy over 10 percent should be investigated.
  2. Whether the results make “intuitive sense.” For example, companies that have previously been using a last-touch methodology may see more credit given to higher-funnel channels on the MTA platform.
Man on laptop

5. Implementing a Crawl, Walk, and Run Approach to Optimization

This is the exciting stage in the process where businesses can start using MTA results to make budget optimizations. However, for many clients, reallocating budgets across channels may be a huge leap, especially if digital channels have previously been managed in silos. A crawl, walk, and run approach is recommended to ensure that business stakeholders are first comfortable with making in-channel budget decisions before moving to cross-channel optimizations.

The “Crawl” phase focuses on a manual shift of budgets within the specific channel, such as putting marketing dollars in the best performing publishers, creative, campaigns, placements, etc. In the Crawl phase, organizations can choose to implement real-time optimization based on MTA results, as many third-party attribution vendors allow for integration with third-party DSPs or search management platforms. 

Finally, the long-term goal for MTA adoption (the “Run” phase) is to be able to allocate budget across channels to maximize overall conversion. This encourages channel owners to work toward a common goal. However, some channels may be given more credit than others based on how thoroughly the channels are tracked (e.g., clicks versus impression tracking), as those with more tracked touchpoints are usually given more credit. Hence, executives should understand the potential tracking limitations before implementing cross-channel optimizations.

 

6. Measuring

Once channels have been onboarded onto the MTA platform, and the organization has aligned on business goals and an optimization schedule, establish a thorough business plan.

Track performance over time

For most of our clients, MTA benefits are rarely realized overnight. For the first few months, let the campaign run without implementing MTA optimizations to establish a baseline MTA benchmark. If the business is highly cyclical, make sure you account for seasonality when setting the benchmark in order to accurately isolate external factors that may impact the campaign. Once a benchmark has been established, start implementing MTA optimizations; keep track of the results over time.

  • As more channels are added into the MTA platform, performance for existing channels will likely change since credit will be redistributed across all touchpoints. It is best to onboard several channels at a time so that the baseline benchmark does not change constantly and muddle the calculated performance lift.

Implement test & learn using MTA results

Organizations can also establish individual tests to identify publishers or tactics that perform best within an MTA environment. 

  • Pre- vs. post-testing: Measure performance for pre- and post-MTA optimization. For instance, if a display publisher is starting to use MTA data for its real-time-bidding strategies, one can assess the potential performance lift before and after RTB integration.
  • Control vs. test. Measure the performance of the test group exposed to MTA optimizations and the control group without MTA optimizations.

 

The effectiveness of using MTA is dependent on the scale of the optimization decisions

Keep in mind that small shifts in budget or MTA optimization decisions will also diminish the potential measurable benefits of MTA.

7. Setting Expectations

MTA offers a sound measurement tool to help marketing and advertising executives make more informed quality decisions. However, MTA is not a panacea. Many of our clients hope that MTA will make optimization decisions for the entire business, but sound media optimization still needs the “human touch.” Due to budget fluctuations, business constraints, publishers’ abilities to scale, or other macro changes, campaigns oftentimes cannot adopt 100 percent of the optimization recommendations made by MTA. For example, if a certain paid search keyword is already in first position, increasing the budget on the particular keyword will not result in incremental conversions. Hence, it is always important to know the campaign constraints. Set expectations prior to using MTA optimizations knowing that the ROI may not be exactly as predicted due to business limitations and unexpected market fluctuations.

 

The benefits of using MTA may not be immediately realized. But with proper implementation, business alignment, and measurement framework, MTA can be a powerful tool that can help companies maximize their advertising dollars and make more informed marketing decisions.

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