Introducing the Definitive Guide to Data-Driven Attribution

Originally Posted on the Adometry M2R Blog
For as many dollars organizations invest in marketing, it never ceases to amaze me how many of those organizations are willing to make guesses about how effectively those dollars are being used. Even when those guesses are educated, they can be way off. We live in a world where data-driven attribution can take the guesswork out of your marketing program to gain a clear and comprehensive view into the customer journey.

It can be intimidating to get started with data-driven attribution. Many marketers are already inundated with data from marketing mix modeling, real-time bidding, website analytics, CRM and more. But the genius of data-driven attribution is that it makes all that other data better, more relevant and actionable to improve the bottom line.

With our Definitive Guide to Data-Driven Attribution, we’ve laid out just how your organization can approach marketing attribution. We’ve made it easy to understand what data-driven attribution does, how it fits in with what you’re already doing and how to get started.

What Is Attribution and What Are the Benefits?

Let’s start with the basics. There are a number of basic models such as first touch, last touch, even and custom attribution. Those models offer general answers across a basic marketing mix, but they fail to provide the true value of each marketing asset as the marketing campaigns get more complex. Today’s cross-channel marketers need a more scientific approach.

Data-driven attribution models use sophisticated algorithms to determine which touch points are the most influential. That means marketers can see the benefits of each touch point and adjust future spending to maximize results.

How Does Data-Driven Attribution Fit into my Analytics Toolset?

Odds are you’re already collecting a ton of marketing and advertising data. That’s great! Data-driven attribution doesn't replace that information. It greatly enhances it.

As an example, let’s look at marketing mix modeling. At the end of a campaign, you look back and assess performance. With data-driven attribution, you can accurately see how each tactic performed so you can plan better for the next campaign. Extending that to the next step, accurate attribution gives you insight that your real-time bidding partners can use to buy top performing ad placements.

Another example is your CRM. As you gain customers, your CRM captures transaction, contact and segment data, but CRMs tend to focus more on customer service and support, not marketing. And although CRMs track multiple channels, they look at lower-funnel activities and offer limited visibility into acquisition and cross-channel marketing in non-direct channels. CRM data is an input that can feed your data-driven attribution solution to yield a more complete picture of customer behavior.


As the graphic above shows (and details more within the guide), data-driven attribution ties all of your other marketing analytics together and improves what you’ve been getting from each one.

Getting Started

Data-driven solutions vary. To get the benefits, you’ll need to ask the right questions about your organization, solidify the right budgets and motivate the right people. In the guide we outline five key steps to getting started.

  1. Define Goals: Consider your current pain points and business goals. Determine the value that all of your marketing activities must deliver for the business and take a holistic view of the data-driven changes you’ll make to meet those goals. That will help determine marketing’s impact on revenue so you can formulate budgets that will yield the highest returns.

  2. Justify Budget: The right solution will pay for itself by creating cross-department efficiencies and increasing the return on each marketing investment, but change can be difficult. Check out the full Definitive Guide for a real-world budgeting exercise to help you promote the benefits of data-driven attribution to key stakeholders.

  3. Be Selective: There are a number of attribution providers. Evaluate them by asking the right questions about their ease of implementation, breadth of services, methodology, capabilities and technology roadmap. Can they handle your data? How will they work with your existing partners, including your ad agency? Do they provide a consultative partnership? Is their model data-driven or rules-based? Are they media agnostic? How is their model validated? Can they measure online and offline activities? How do they account for multi-screen customer journeys? How often do they upgrade their solution?

  4. Get Prepared: Picking a provider is a good start, but you also must get ready for integration. Prepare both human and data resources to hit the ground running. Evaluating data readiness and preparing stakeholders ahead of time will help you determine how much support you’ll need during implementation.

  5. Evaluate Success: Your stakeholders will be more invested in driving success with data-driven attribution if they can envision what success looks like, and concretely evaluate whether goals are being achieved. Show them the way. Leverage your goals to evaluate your provider’s performance on marketing performance, enterprise ability, ease and flexibility, quality of output, total cost of ownership and an innovative roadmap.
There’s no doubt that today’s marketers need better performance measures to know whether they are producing the best results for the organization. Data-driven attribution requires investment on the front end, but it pays big rewards that will have you asking why you didn’t take the plunge sooner.

We encourage you to dive deeper to help your organization understand the true benefits and implications of data driven attribution through our definitive guide.

Referensi: Google Analytics Blog - Introducing the Definitive Guide to Data-Driven Attribution.