Marketers and CI professionals frequently tell us that they want a better measurement technique to accurately determine the true performance of channels and customers. I am pleased to announce that today we published The Forrester Wave™: Cross-Channel Attribution Providers, Q2 2012. This vendor review is a result of countless hours of vendor reviews and assessments, in-person briefing reviews, customer calls, fact checking, and countless hours of intensive research work.
After long days and countless Starbuck lattes, I crawled out of this very intense research process, and a few key takeaways emerged:
Companies are investing in attribution. Marketers are seeking expert advice for the best ways to measure their channels with more precision. Attribution approach can provide a more concise way of measuring true channel and customer performance. And that’s something organizations are hungry for. To do this, they need help developing attribution models and making sense of all their data.
Cross- channel attribution is a relatively immature market. Vendors have fairly immature cross-channel attribution offerings. Most continue to emphasize digital attribution but are rapidly expanding to include additional channels, while also developing future marketing scenario-planning capabilities.
I’ve been on the CI team for a few years in a supporting role and, more recently, working behind the scenes with Suresh Vittal to drive our research around loyalty. I’m excited to announce that, going forward, I will be the analyst leading our coverage of the technologies, services, and analytics that support customer loyalty.
My first report in this new role will provide best practices on building a world-class loyalty program. Then keep an eye out for an analysis of existing and emerging loyalty program features. Future research will dive into topics that include reward design, revenue models for loyalty programs, the future of loyalty, and more Wave evaluations of the loyalty vendor ecosystem.
I am looking forward to getting to know many of you better and following the evolution of this exciting space. Whether you have insights to share, questions to ask, or loyalty technology and services that you want to tell me about, I want to hear from you! Please engage with me via our Inquiry and/or Briefing teams, or track me down at Forrester’s upcoming Customer Intelligence Forum (April 18-19 in Los Angeles).
It’s been a week since I got back from SxSW in Austin, and I still can’t believe how absolutely MASSIVE the coverage of privacy, personal data, and identity issues was at the conference. By my count, there were some two dozen sessions, including the Core Conversation I led, across a range of topics that are central to the principles of personal identity management (PIDM).
Photo of PIDM Core Conversation courtesy of Doc Searls
Some of the most interesting takeaways from my perspective:
1. We need a consumer bill of rights that’s defined and ratified mutually by individuals and industry. We need adoption convergence by both groups if PIDM is to succeed in a mutually beneficial manner.
2. We need more cross-functional working groups that include marketers, policy wonks, technologists and consumer advocates. Regulators are simply not going to be able to address the needs and responsibilities of all parties, nor the practical and technological challenges this massive problem faces today.
3. We desperately need guidelines and best practices for privacy policies, governance, and acceptable use of consumer data. By and large, most of the marketers and business people I spoke with WANT to do the right thing, but they’re just not sure what that means right now.
Companies adopt advanced analytics tools and techniques to convert data into intelligence and drive key customer-facing business decisions. We see that customer intelligence (CI) professionals involved in customer analytics broadly perform three activities:
Generate analytics: Create and produce analytical insights using analytical tools and technologies.
Apply analytics: Choose the appropriate analytical methodology for the business problem and apply it to the context of the customer lifecycle.
Activate analytics: Use analytical output and insights to optimize customer experiences and to drive customer growth, share of wallet, retention, and lifetime value.
The essential shape of the enterprise marketing landscape hasn’t changed much over the years. In last week’s Revisiting The Enterprise Marketing Software Landscape, I dissect technologies into the four basic categories of marketing management, brand management, relationship marketing, and interactive marketing. Consumers are rapidly changing behaviors, and marketing as a practice is evolving dramatically, but the technologies that marketers buy continue to come in essentially the same containers.
Notice, however, all of the decision management systems employed across the marketing landscape. From interaction management to online testing to recommendations to contact optimization, marketers are using automated systems to make an increasing number of customer-facing decisions. Viewed from the perspective of those decisions, the landscape of marketing technologies is shifting under our feet.
So is it time for a new take – say, customer decision management (CDM) – on marketing technology?
Any big data or analytics conversation would be remiss without the mention of "data scientists." Much has been written about data scientists– who they are, who they should be, and where to find them. My colleague James Kobielus wrote an interesting series of blog posts about the skills required to become a data scientist.
From a customer intelligence (CI) perspective, we outlined four segments of CI professionals — marketing practitioners, marketing technologists, marketing scientists, and customer strategists. Of these, marketing scientists typically orchestrate the customer and marketing analytics function. They manage the reporting, analysis, and predictive modeling processes using marketing and customer data.
In a CI context, we find that the role of the marketing scientist has evolved from being a pure data analyst drowning in data analysis to that of an analytics translator — someone who is equally comfortable with building advanced predictive models and also adept at embedding the output of the models into customer-facing processes. What type of marketing scientist does your analytics team have?
We recently published a report on why "Customer Intelligence Needs A New Breed Of Marketing Scientist" (accessible to Forrester clients). In the report, we highlight ways to develop analytics translators across the staffing cycle — starting from attracting the right talent, nurturing the relevant skills, training with new skills, and incenting them based on business impact.
Yesterday, the White House released a long-awaited set of recommendations that are focused on helping individuals take greater control of how their data is collected and used for online marketing purposes. It includes what's being referred to as a "Consumer Privacy Bill of Rights."
The language is vague. The timeline to completion is long. The guidelines, for now, are "opt-in" for organizations. All true.
But folks? The glory days of scraping and selling and repurposing customer data are over. The Oval Office has spoken on the issue of privacy and personal data, and its bill of rights is crystal clear: Tell me what you’re collecting, how you’re using it, protect it well, give me a copy, and give me a chance to correct it, delete it, or opt out entirely.
Does your firm use customer analytics to optimize relationship marketing efforts? Does your firm use analytical techniques to understand and predict customer behavior? If so, we want to hear from you.
We are launching our first Customer Analytics Adoption Survey for customer analytics users. With this survey, we want to understand how you use and apply customer analytics in your organization. In particular, we’re fielding questions to understand the goals and challenges with using customer analytics, the descriptive and predictive analytics techniques and models you use, the business impact of customer analytics, the customer metrics you track, and how you prioritize customer analytics initiatives across the customer life cycle. We encourage you to participate in this survey, as this information will help you benchmark your customer analytics adoption against peers and assess future opportunities.
We're looking for a new analyst to join Forrester's Consumer Product Strategy practice. Are you experienced in the field of product planning, development, and innovation? Do you have an insatiable curiosity for where the digital economy is headed and how digitally disruptive products are changing the world in which we live? If this sounds like you, keep reading . . .
Digital disruption is transforming consumer products, inverting industry economics, and redefining customer relationships for companies in all industries. Forrester is helping our clients adapt their businesses and innovate their products in response to the unprecedented pace of technology change that characterizes this revolution. We need a Senior/Principal Analyst with cross-industry experience to join the team and help serve Forrester’s clients with forward-looking research and advice on how product strategists can capitalize on digital disruption.
If you’re interested, apply online. We look forward to hearing from you!
As a new analyst at Forrester, I’m taking over coverage of cross-channel attribution, metrics, and measurement for customer intelligence professionals. It is a wide-spanning topic to cover, but I’m up for the challenge!
One of the major topics that I’ll cover is cross-channel attribution. Cross-channel attribution is essentially an advanced measurement approach to measure channel performance and customer performance metrics more accurately by calculating the true credit given to a specific marketing effort that leads to a desired customer action. It’s a daunting task for marketers because it requires organizational support and a deep understanding of attribution modeling.
For support, marketers often turn to external vendors — the subject of my latest research: Understanding the Cross-Channel Attribution Landscape. As I was researching this report, it was clear that cross-channel attribution is top of mind for marketers and CI folks alike. Why? It’s a more advanced, precise way to measure channel and customer performance. In an age of austerity that requires responsible and efficient marketing investment, it’s no wonder that it’s a priority.