Buy analytics software, hire marketing scientists, and engage analytics consultants. Now wait for the magic of customer analytics to happen. Right?
Wrong. Building a successful customer analytics capability involves careful orchestration of several capabilities and requires customer insights (CI) professionals to answer some key questions about their current state of customer analytics:
What is the level of importance given to customer analytics in your organization?
Have you clearly defined where you will use the output of customer analytics?
How is your analytics team structured and supported?
How do you manage and process your customer data?
Do you have clear line of sight between analytics efforts and business outcomes?
What is the process of sharing insights from analytics projects?
What type of technology do you need to produce, consume and activate analytics?
Last week, I had the pleasure of attending the Future of Consumer Intelligence conference in San Francisco. This week, when I reflect back on the conference topics and energy, I realize how fitting San Francisco was as the location of the event: Much like the essence of the city itself, the conference speakers and attendees showed ingenuity and optimism around the challenges and opportunities that the market research industry faces. I also thought about the same conference that I attended last May (IIR Market Research Technology Event 2012) and the key themes that I gathered and blogged about: Big data is here, integrating survey and behavioral data is powerful, and behavioral economics has huge implications for market research. For me, the big difference between last year’s conference and this year’s is this: A year ago, market insight professionals were sizing up their challenges with the future of market research. This year, they are taking the bull by the horns and embracing both the challenges and opportunities that technology in market research presents. Here are the main themes I gathered from the event:
As an analyst on Forrester's Customer Insight's team, I spend a lot of time counseling clients on best-practice customer data usage strategies. And if there's one thing I've learned, it's that there is no such thing as a 360-degree view of the customer.
Here's the cold, hard truth: you can't possibly expect to know your customer, no matter how much data you have, if all of that data 1) is about her transactions with YOU and you 2) is hoarded away from your partners. And this isn't just about customer data either -- it's about product data, operational data, and even cultural-environmental data. As our customers become more sophisticated and collaborative with each other ("perpetually connected"), so organizations must do the same. That means sharing data, creating collaborative insight, and becoming willing participants in open data marketplaces.
Now, why should you care? Isn't it kind of risky to share your hard-won data? And isn't the data you have enough to delight your customers today? Sure, it might be. But I'd put money on the fact that it won't be for long, because digital disruptors are out there shaking up the foundations of insight and analytics, customer experience, and process improvement in big ways. Let me give you a couple of examples:
The deluge of customer data shows no signs of abating. The perpetually-connected customer leaves data footprints in every interaction with a brand. This presents tremendous opportunities for customer insights professionals and analytics practitioners tasked with analyzing this data, to not only get smarter about customers but ensure that the insights get appropriately used at the point of customer interaction.
When we asked customer analytics users about the challenges and drivers of customer analytics adoption, we found that data integration and data quality continue to inhibit better adoption of customer analytics while users still want to use analytics to improve the data-driven focus of the organization and drive satisfaction and customer retention.
Forrester’s Customer Analytics Playbook guides customer insights professionals, marketing scientists and customer analytics practitioners into this new reality of customer data and helps discover analytics opportunities, plan for greater sophistication, take steps towards building a customer analytics capability and continually monitor progress of analytics initiatives. It will include 12 chapters (and an executive overview) that cover different aspects of customer analytics.
When we set out to evaluate the new breed of firm that we call "customer engagement agencies," we sent our initial screener to an incredibly long list of firms -- over sixty, in fact! -- ranging from MSPs to digital agencies to management consultancies. We felt that we needed to cast a wide net if we wanted to understand the range of approaches vendors take to customer engagement: how they use data and analytics, the channels they enable with customer intelligence, and how they service their most strategically engaged clients. As the responses rolled in, a hypothesis began to take shape in my mind: The emerging customer engagement agency model hails from two mature markets -- digital/direct agencies and database MSPs -- and, depending on provenance, these evolving agencies take one of two primary approaches to customer engagement.
Turns out, I was on the right track, though the reality is not quite so black and white.
In our final evaluation of 13 vendors in The Forrester Wave: Customer Engagement Agencies, Q4 2012, we did find different strengths and weaknesses depending on legacy business model, but ultimately EVERY firm still has a long road ahead of evolving its people and processes to support CEA clients. We also found, though, that each CEA we evaluated is working hard to connect the dots between strategy, analytics and execution in order to optimize customer experience and profitability. And that can only be a good thing for the marketers and CI leaders who are visionary enough to hire them.
Customer Intelligence (CI) professionals invest in data-mining, predictive analytics and modeling tools and technologies to make sense of the deluge of data. In the past, they've had to adapt horizontally-focused analytics and modeling solutions to a customer intelligence and marketing context. Today, however, they can consider a gamut of customer analytics and marketing-focused analytics providers that have not only analytics production expertise but also domain and role-focused expertise.
We just published our first evaluation focusing on the customer analytics category here: The Forrester Wave™: Customer Analytics Solutions Q4 2012 . After screening more than 20 providers for analytics products specifically catering to customer analytics applications, we identified and scored products from six of the most significant providers: Angoss Software, FICO, IBM, KXEN, Pitney Bowes, and SAS. Our evaluation approach consisted of a 70-criteria evaluation; reference calls and online surveys of 60 companies; executive briefings; and product demonstrations. The core criteria included key dimensions such as core functionality (data management, modeling, usability); analytics production; analytics consumption; analytics activation and customer analytics applications. The evaluation also included the strength of the current product and corporate strategies in the customer analytics market as well as the future vision for this category.
We found that four competencies define the current customer analytics market:
ExactTarget today announced plans to acquire two companies: Pardot and iGoDigital. The acquisitions signal that ExactTarget, only recently public, intends to use its cash reserves to grow aggressively against the competition in revenue, market segments, and features. So what does it mean?
Are the two acquisitions related?
No, the dual acquisitions are a quirk of timing, allowing ExactTarget to drive the marketing technology conversation in advance of Connections, its user conference in Indianapolis next week. I’ll separate my comments to better address each.
Still, I’ll risk a theme for these two acquisitions: Marketing automation without predictive analytics is blind, but analytics without automation is empty.
Why did ExactTarget make the acquisitions now?
The acquisition is unlikely to make a big impact in the short term. Recommendations are a small part of the marketing software mix for retailers. ExactTarget can cross-sell online recommendations into its significant B2C base, but in the end, ExactTarget is acquiring the firm for a longer-term move.
Eighteen months ago, when I started down the path of what would become our body of Personal Identity Management (PIDM) research, there were only a few customer intelligence professionals who gave much credence to the picture we were painting. What a difference a year makes. Today, privacy, data governance, consumer empowerment, and understanding "the creepy factor" are core to the conversations I have with CI pros in both marketer and vendor organizations.
At the center of those conversations is often the question, "Who are the players in tomorrow's consumer data ecosystem?" We've just published a report, Making Sense of a Fractured Consumer Data Ecosystem, that reviews the strengths and weaknesses of four existing vendor categories plus three emergent business models. These include:
Consumer data giants: Companies, like Acxiom, Epsilon, Experian, and Infogroup, that have an opportunity to become consumer-friendly data managers but are at greatest regulatory risk
Reputation management providers: Companies, like Intelius and Reputation.com, that could help consumers manage data access but need to focus on their B2C business models to do so
Online services giants: Companies, like Google, MSN, and Yahoo, that already have access to highly personal data but serve too many masters
I’m excited to announce that our new research on how firms use customer analytics was just published today. The new research reveals some interesting findings:
Customer analytics serves the customer lifecycle , but measurement is restricted to marketing activities. While customer analytics continues to drive acquisition and retention goals, firms continue to measure success of customer analytics using easy-to-track marketing metrics as opposed to deeper profitability or engagement measures.
Finding the right analytics talent remains challenging . It’s not the just the data. It’s not the just technology that hinders analytics success. It’s the analytical skills required to use the data in creative ways, ask the right questions of the data, and use technology as a key enabler to advance sophistication in analytics. We’ve talked about how customer intelligence (CI) professionals need a new breed of marketing scientist to elevate the consumption of customer analytics.
CI professionals are keen to use predictive analytics in customer-focused applications, Forty percent of respondents to our Global Customer Analytics Adoption Survey tell us that they have been using predictive analytics for less than three years, while more than 70% of respondents have been using descriptive analytics and BI-type reporting for more than 10 years. CI professionals have not yet fully leveraged the strengths of predictive analytics customer applications.
We've spent a lot of time in the past year looking at how the customer intelligence services landscape is changing. For one thing, it's a heck of a lot more chaotic: everyone from management consultants to systems integrators to KPO vendors is putting a stake in the ground of CI services. We've also seen a dramatic shift in the way some digital & direct agencies and database MSPs are thinking about their most strategic client relationships. This change has been so noticeable that, a few months ago, we actually published research that defines a new business model: The Customer Engagement Agency (CEA).
It's no surprise that clients and vendors alike are excited about this model. These agencies help elevate customer intelligence within the client organization. They bring attention and focus to the importance of customer knowledge, and they work hard at infusing that knowledge throughout every customer touchpoint. They measure customer value, not just marketing campaigns. And they help clients use CI to answer questions about everything from product development to logistics and resource management.
But, this is an emerging market — the players are evolving from very different backgrounds; they offer substantially different "value-added" capabilities; and many of them have proprietary methods and models that make it hard to compare apples to apples.
That's why we've just kicked off a Customer Engagement Agency WaveTM that will publish in the fall. If you're intrigued with the idea of working with a CEA, I encourage you to: