Choosing a Multi-Attribution Analytics Solution

Transcription

1 Choosing a Multi-Attribution Analytics Solution Page 1 of 10

2 Published by Convertro Inc 1453 Third Street Promenade Suite 370 Santa Monica, CA Main: (800) Fax: (888) Copyright 2011 Convertro, Inc. All rights reserved. Page 2 of 10

3 Executive Summary Online marketing with its promise of total measurement and complete transparency has grown at a fast clip over the years. But in the recent past this same measurability has led to frequent questioning of the efficiency of digital marketing. Marketers reach target customers in a variety of ways, across a variety of channels. Astute marketers have come to realize that last click/first click attribution is flawed and results in misallocation of marketing budgets by providing only partial insight. Multi-attribution, initially explored by only a few innovative start-ups, has now gained traction among seasoned analytics providers who are all trying to compete with one another and with the existing multi-attribution solutions in offering their own flavor of multi-attribution. With so many options in the market, it is important for firms to understand the key differences in offerings and evaluate them in the context of their own requirements. This white paper gives you a concise yet comprehensive checklist to assist you in selecting a multi-attribution solution that best meets your needs. What is Multi-Attribution? Marketers use multiple media to reach audience: according to a Microsoft Atlas Institute study, 93-95% of all touch points are ignored when you attribute conversions to the last click 1. Consider the case of a homeowner trying to buy custom modern lighting. As a first stop, he conducts a search on modern lighting, and is served PPC ads from several ecommerce companies including YLighting. He then does an organic branded search, visits the YLighting website, looks at a few products, and leaves before making a decision. He is retargeted a few days later, comes back to the web site, identifies a product to buy, leaves to search for YLighting coupons, comes back through an affiliate site and eventually completes the transaction. This simple example is a classic case for multi-attribution and is typical behavior in online transactions. Yet most analytics packages use last click attribution by default, resulting in the affiliate getting credit for the sale. All the assists in the form of PPC, organic search, SEO, retargeting fail to get any credit. In contrast, Multi-attribution understands and accounts for the fact that a classic marketing campaign touches potential customers in multiple ways. Multi-attribution tools track all marketing sources that the customer was exposed to before the purchase, and apportion credit among all these sources. That said, within Multi-attribution, there are different frameworks for allocating credit: 1. Even Credit Simply split the credit for the sale evenly among all known sources 1 Page 3 of 10

4 2. Funnel Position Categorize sources as introducers (the first known source in the path to conversion), influencers (sources in the middle of the funnel) and closers (last known source before conversion) and apportion credit among them based on marketers preferences/beliefs on which is more valuable. 3. Custom Custom business rules that apportion credit based on custom requirements. 4. Algorithmic Sophisticated statistical models involving regression/hypothesis testing to arrive at a model taking time decay into account. Top Criteria As you realize the inadequacy of last click attribution, and make the transition to multiattribution, make sure you ask tough questions in the following areas to ensure that the solution you pick is a good fit for your requirements. Data Quality Insights Campaign Management Flexibility & Customization Transparent Attribution Models Fraud Detection/Forensics Tag Container & Selective Pixel Firing Ease of Deployment Selection Process As with any selection process there are distinguishable phases described below. Identify the pain points and shortcomings of your current analytics implementation Make a list of weaknesses of your current analytics/marketing measurement system and understand how it constrains true campaign measurement. Make a list of insights you would like and cross check with current capabilities. Shortlist the minimum requirements for consideration Go over the feature wishlist to come up with a list of minimum requirements that are needed for you to switch from your current implementation. Research analytics providers and compare them using the framework provided below. Page 4 of 10

5 The checklist provided is quite comprehensive, and you may not need the analytics solution to check off on every single item. But, in order for your analytics solution to accommodate your growing needs over the years, it is essential that it checks off on most of them. Avoid making the following mistakes often made during vendor selection. o Following the lemmings Don t pick a solution just because everyone else in the industry seems to be picking it. A solution has to fit your needs and provide solutions to your unique problems. The reason why most firms go with the majority opinion is that it serves as an endorsement for their decision and helps deflect criticism in the future. By refusing to be a lemming you can guarantee that you will make a better choice that provides you with better benefits. o Preferring form over substance Often decisions are made based on data presentation with less consideration to underlying data quality. Choosing form over substance is a definite and unobstructed path to failure. Form is critical, but substance is more so. Make sure that your analytics package is backed by granular and quality data. o Investing in a product vs. a partner Analytics packages can never be entirely automated. To arrive at actionable, powerful insights you need a partner to guide you through the analysis. Most analytics packages are nothing more than a data dump. To use this data effectively, you need not just another software vendor, but rather a partner who is truly committed to your success and helps you analyze and derive insights from data. o Selecting a product with teaser rates that lock you into higher rates in the future Don t make the mistake of selecting a product that offers teaser-pricing for the first few billing cycles but locks you into steep increases thereafter. Make sure that the pricing is simple and transparent. o Buying a product that is too complex and not transparent A product that is too complex to explain to senior management is more of a black box, and will always be questioned. When you do not understand how a specific recommendation is being made, then it is not easy to trust it to be reliable. Evaluate using demos and trial versions A final step in the evaluation process is to schedule product demos. Make sure to ask questions and seek clarifications. If possible, use a trial version to familiarize with the feature set and to accurately compare offerings. Page 5 of 10

6 DATA QUALITY Data is King. We know from experience that data is more persistent than the applications built around it. The application is nothing more than a way to visualize data and although it can and does change over time, quality data is quasi-permanent and continues to provide insights far beyond its projected useful life. Does the product account for cookie deletions, use of multiple browsers or devices and track users across multiple sessions? Does the product store data at a granular level including click/order data vs. store it in an aggregated form? Does the product truncate/age out data to save on costs? Does the product report on all known sources for a conversion without limiting them to a ad-hoc number, such as 5/10 or to a specific cookie length? Data is only as good as the ability to identify users uniquely over long periods of time. Robust tracking is critical for getting comprehensive information about campaigns a user is exposed to. Having granular data means you can always rerun analysis with new models/frameworks to gain additional insight as the business evolves. It is your data and having all of it helps compare performance of changes year-overyear and through business strategy changes more effectively Limiting to a set number results in losing out information on valuable introducers and influencers in the source funnel DEEP INSIGHTS A good analytics solution should lead to insights, not just a data dump of information 2. You should be able to separate the chaff Does the product give true insights into marketing management or is it more of a reporting tool? Does the product result in growth and ROI/ROAS improvement or is it just an added expense? Reporting is different from Analytics. A pure data dump is not analytics and the product should provide you with actionable insights and analysis that allow you to grow your business The product should provide quantifiable results and an easy way to verify actual vs. expected lift of recommended changes. CAMPAIGN/MARKETING MANAGEMENT Great insights don t translate into great results if they don t easily drive campaign management systems such as bid management, retargeting, creative optimization, etc. Does the product integrate well with campaign/bid management tools? Does the product have an ability to integrate with retargeting, creative and landing page optimization tools? Does the product allow you to measure campaign/channel/vendor performance? The recommendations should populate PPC bid management so you can optimize spend The product should integrate the results with the display ads and landing pages and optimize them. By measuring and stacking vendors against one another, you can revisit vendor payment 2 Page 6 of 10

7 Does the product give you insights into accretive vs. cannibalistic sources? Does the product give you insights into the lifetime value of channels based on their ability to drive repeat customers? agreements to align with their true contribution. The tool should have built in forensic analytics to determine which sources are accretive and which are cannibalistic, so you can increase spend on accretive and decrease/eliminate cannibalistic sources. Some sources are better at driving repeat customers and the tool should be able to calculate the true LTV based on such insights. FLEXIBILITY AND CUSTOMIZATION Allow exceptions to the rule for exceptional results or when circumstance demands 3. one size fits all. Make sure the solution is flexible with well thought out built-in models that you can easily pick from. An ability to use one model for budgeting decisions but another one for payout is critical since merchants have varied revenue sharing agreements with their vendors. Does the product allow for flexibility in attribution modeling allowing you to choose between in-built models such as multi-even, funnel, last, first etc.? Is the product flexible enough to allow you to use multiple models at the same time? Does the product allow you to build custom attribution models easily? Does the product allow you to use custom cookie windows for analyzing channels and vendors for payouts? Does the product have the ability to report on both financial and brand related metrics such as engagement, loyalty etc? Does the product allow you to change attribution methodologies and/or source taxonomy either retro actively or going forward? Does the product have the ability to track offline conversions? Does the product allow you to import historical data and/or conversion data Revenue split agreements with vendors differ vastly and you need your models to be flexible. Comparison of the different models side by side helps you better optimize your revenue sharing agreements with vendors. Built in models might sometimes limit you or try to force-fit your unique business model and strategy to a few known and used models. You need to be able to customize attribution models to be truly relevant for your business The tool needs to allow you to set custom cookie length so that you can accurately value vendors and channels and assess if you are under/over paying them A vendors true worth can only be measured by having insight into both financial and branding effects. As you gain insight from the data, you might want to tweak the model for a better fit. Instead of being limited to changes only going forward, you should have the ability to reanalyze past conversion data with the enhanced attribution model. Most retailers have offline transactions that are often ignored by web analytics products. But not tying this channel in will cause you to lose valuable insight on the efficacy of your marketing The solution should allow you to import data from a prior implementation and also sales 3 John Wooden Page 7 of 10

8 after the sale? Does the product track display advertising effectively by capturing view-through conversions? data that might not integrate in real-time. Display does not work the same way as search does, and usually might not result in immediate click-through visits to the website. If the solution is not integrated with ad servers to track view-through conversions, then you might be shortchanging the effect of display TRANSPARENT ATTRIBUTION MODELS Don t choose a black box model that cannot be audited or validated. It needs to be easy to understand and to explain. Are the attribution modeling and algorithms transparent and easily verifiable? Is the product simple and easily understandable? Transparency and verifiability are keys for trust. When you intend to make business decisions based on this data, you need to be able to verify and re-verify it. All effective models are easy to understand and explain. This becomes especially critical when you have to explain increase/decrease in marketing spend to executive management based on recommendations from the multi attribution tool. FRAUD DETECTION/FORENSICS Online fraud is a reality and a good analytics solution should help in enforcing channel contract guidelines in order to reduce/avoid it. Does the product allow you to detect affiliate/vendor fraud? Does the product give you clear indication of overlap among sources driving conversions, so you can optimize your spend? Does the product have the ability to recognize sources that enhance brand value? The tool needs to report on fraud so you are not overpaying for resources that are stealing credit from others and obfuscating the utility of your analytics reports. On average, each user is exposed to about 3.3 sources before they convert, and having an insight into how these sources overlap (for example, a report which details which sources often work together in getting a visitor to convert, and how often they overlap with others vs. operate independently) can help you optimize your spend. All marketing might not have a direct and immediate effect on ROI. Some of the sources may be brand enhancers that deliver financial gain in the longer run. The analytics solution needs to detect and report on those sources so you can optimize your mix of brand-enhancing marketing and direct ROIbased marketing. Page 8 of 10

9 TAG CONTAINER & SELECTIVE PIXEL FIRING A universal tag container with selective pixel firing is required for policing and enforcing business rules. Does the product provide a universal tag container for easy deployments of pixels and tags? Does the product use the tag container to ensure faster page load times, allowing for validation of security and latency? Is the tag container customizable with configurable live/expiry dates for tags? Is the tag container testable prior to deployment? Does the tag container provide support for business rules to dictate the selective firing of pixels/tags? Does the tag container provide detailed reports on tags that were fired (not tags that did not fire) on an event? Is the tag container flexible to allow for ordering/dependency creation for business rules based tag management? Does the system provide an easy to manage interface for the tag container so a single tag can be deployed across multiple sites/pages/events or selectively based on business rules? Having a universal tag container provides multiple benefits to the client: Faster page load times time out tags that don t respond within set times Verification of SSL certificates and clean up of offending tags Quicker and easier tag management including add, remove, modify tags independent of site/page design. Implementation of custom business rules to align with vendor agreements Robust reporting on which tags fired as expected, which ones misfired etc., Integrates well with analytics solution so business rules can be easily modified based on channel performance. EASE OF DEPLOYMENT IT resources at most ecommerce companies are already tightly constrained and don t have the flexibility to allocate dedicated resources for managing web analytics solutions. As such, ease of deployment and maintenance become extremely critical for deriving full benefit. Is the analytics solution easy to deploy? Is the analytics solution easy to maintain on an ongoing basis when new web pages are deployed and/or changes are made for conversion and event tracking? Complexity results in deployment mistakes and can result in incorrect/missing data. Web pages, business rules and processes constantly change and maintenance of tags/mechanism used for tracking should be easy enough so IT departments are not overly constrained. Page 9 of 10

10 Final Thoughts There are several solutions in the market, and each has its own strengths. A true comparison of channels requires that all customer touch points be accurately accounted for. Data quality must be the number one criteria and as any former student of statistics remembers: given the choice between better data and a better algorithm, always choose better data. The reason being, that if the analysis is based on insufficient or flawed data, then the conclusion will be inherently wrong regardless of the sophistication of the visualizations or black box approaches. In addition, the ability to make actionable those insights on what is working and what is not is clearly the difference between just another analytics package versus incremental profit and revenue. Solutions that integrate into existing marketing management software, provide specific recommendations and quantify the impact will provide the highest return on investment irrespective of cost. Page 10 of 10