The Spectrum of Data Sources for Marketers Is Wide (& Overwhelming)
I’ve been using an anecdote of late that Malcolm Gladwell supposedly related at a SAS user conference earlier this year: over the last 30 years, the challenge we face when it comes to using data to drive actions has fundamentally shifted from a challenge of “getting the right data” to “looking at an overwhelming array of data in the right way.” To illustrate, he compared Watergate to Enron — in the former case, the challenge for Woodward and Bernstein was uncovering a relatively small bit of information that, once revealed, led to immediate insight and swift action. In the latter case, the data to show that Enron had built a house of cards was publicly available, but there was so much data that actually figuring out how to extract the underlying chicanery without knowing exactly where to look for it was next to impossible.
With that in mind, I started thinking about all of the sources of data that marketers now have available to them to drive their decisions. The challenge is that almost all of the data sources out there are good tools — while they all claim competitive advantage and differentiation from other options…I believe in the free markets to the extent that truly bad tools don’t survive (do a Google search for “SPSS Netgenesis” and the first link returned is a 404 page — the prosecution rests!). To avoid getting caught up in the shiny baubles of any given tool, it seems worth organizing the range of available data some way — put every source into a discrete bucket. It turns out that that’s a pretty tricky thing to do, but one approach would be to put each data source available to us somewhere on a broad spectrum. At one end of the spectrum is data from secondary research — data that someone else has gone out and gathered about an industry, a set of consumers, a trend, or something else. At the other end of the spectrum is the data we collect on our customers in the course of conducting some sort of transaction with them — when someone buys a widget from our web site, we know their name, how they paid, what they bought, and when they bought it!
For poops and giggles, why not try to fill in that spectrum? Starting from the secondary research end, here we go…!
Secondary Research (and Journalism…even Journalism 2.0)
This category has an unlistable number of examples. From analyst firms like Forrester Research and Gartner Group, to trade associations like the AMA or The ARF, to straight-up journalists and trade publications, and even to bloggers. Specialty news aggregators like alltop.com fall into this category as well (even if, technically, they would fit better into a “tertiary research” category, I’m going to just leave them here!).
I stumbled across iconoculture last week as one interesting company that falls in this category…although things immediately start to get a little messy, because they’ve got some level of primary research as well as some tracking/listening aspects of their offer.
Moving along our spectrum of data sources, we get to an area that is positively exploding. These are tools that are almost always built on top of a robust database, because what they do is try to gather and organize what people — consumers — are doing/saying online. As a data source, these are still inherently “secondary” — they’re “what’s happening” and “what’s out there.” But, as our world becomes increasingly digital, this is a powerful source of information.
One group of tools here are sites like compete.com, Alexa, and even Google’s various “insights” tools: Google Trends, Google Trends for Websites, and Google Insights for Search. These tools tend to not be so much consumer-focussed as site-focussed, but they’re getting their data by collecting what consumers are doing. And they are darn handy.
“Online listening platforms” are a newer beast, and there seems to be a new player in the space every day. The Forrester Wave report by Suresh Vittal in Q1 2009 seems like it is at least five years old. An incomplete list of companies/tools offering such platforms includes (in no particular order…except Nielsen is first because they’re the source of the registration-free PDF of the Forrester Wave report I just mentioned):
- Nielsen Buzzmetrics
- Alterian/Techrigy SM2
- Crimson Hexagon
- Collective Intellect
And the list goes on and on and on… (see Marshall Sponder’s post: 26 Tools for Social Media Monitoring). Each of these tools differentiates itself from their competition in some way, but none of them have truly emerged as a sustained frontrunner.
I put web analytics next on the spectrum, but recognize that these tools have an internal spectrum all their own. From the “listening/collecting” side of the spectrum, web analytics tools simply “watch” activity on your web site — how many people went where and what they did when they got there. Moving towards the “1:1 transactions” end of the spectrum, web analytics tools collect data on specifically identifiable visitors to your site and provide that user-level specificity for analysis and action.
Google Analytics pretty much resides at the “watching” end of this list, as does Yahoo! Web Analytics (formerly IndexTools). But, then again, they’re free, and there’s a lot of power in effectively watching activity on your site, so that’s not a knock against them. The other major players — Omniture Sitecatalyst, Webtrends, Coremetrics, and the like — have more robust capabilities and can cover the full range of this mini-spectrum. They all are becoming increasingly open and more able to be integrated with other systems, be that with back-end CRM or marketing automation systems, or be that with the listening/collecting tools described in the prior section.
The list above covered “traditional web analytics,” but that field is expanding. A/B and multivariate testing tools fall into this category, as they “watch” with a very specific set of options for optimizing a specific aspect of the site. Optimost, Omniture Test&Target, and Google Website Optimizer all fall into this subcategory.
And, entire companies have popped up to fill specific niches with which traditional web analytics tools have struggled. My favorite example there is Clearsaleing, which uses technology very similar to all of the web analytics tools to capture data, but whose tools are built specifically to provide a meaningful view into campaign performance across multiple touchpoints and multiple channels. The niche their tool fills is improved “attribution management” — there’s even been a Forrester Wave devoted entirely to tools that try to do that (registration required to download the report from Clearsaleing’s site).
At this point on the spectrum, we’re talking about tools and techniques for collecting very specific data from consumers — going in with a set of questions that you are trying to get answered. Focus groups, phone surveys, and usability testing all fall in this area, as well as a plethora of online survey tools. Specifically, there are online survey tools designed to work with your web site — Foresee Results and iPerceptions 4Q are two that are solid for different reasons, but the list of tools in that space outnumbers even the list of online listening platforms.
The challenge with primary research is that you have to make the user aware that you are collecting information for the purpose of research and analysis. That drops a fly in the data ointment, because it is very easy to bias that data by not constructing the questions and the environment correctly. Even with a poorly designed survey, you will collect some powerful data — the problem is that the data may be misleading!
Beyond even primary research is the terminus of the spectrum — it’s customer data that you collect every day as a byproduct of running your business and interacting with customers. Whenever a customer interacts with your call center or makes a purchase on your web site, they are generating data as an artifact. When you send an e-mail to your database, you’ve generated data as to whom you sent the message…and many e-mail tools also track who opened and clicked through on the e-mail. This data can be very useful, but, to be useful, it needs to be captured, cleansed, and stored in a way that sets it up for useful analysis. There’s an entire industry built around customer data management, and most of what the tools and processes in that industry focus on is transaction data.
As much as I would like to wrap up this post by congratulating myself on providing an all-encompassing framework…I can’t. While there are a lot of specific tools/niches that I haven’t listed here that I could fit somewhere on the spectrum of tools as I’ve described it, there are also sources of valuable data that don’t fit in this framework. One type that jumps out to me is marketing mix-type data and tools (think Analytic Partners, ThinkVine, or MarketShare Partners). I’m sure there are many other types. Nevertheless, it seems like a worthwhile framework to have when it comes to building up a portfolio of data sources. Are you getting data from across the entire spectrum (there are free or near-free tools at every point on the spectrum)? Are you getting redundant data?
What do you think? Is it possible to organize “all data sources for marketers” in a meaningful way? Is there value in doing so?