Three Free and Not-so-Free "Listening" Sites

I've talked about "listening" or inbound marketing as a key component of a marketer's job in the late 2000's environment, and I thought it would be helpful to aggregate a few of the sites that have interesting ideas on the listening front. What I do to keep all of these listening sites organized is to use http://www.delicious.com/ (formerly de.licio.us) and tag each of the listening sites so I can keep them as a group or sort through them based on what I'm looking for.

1. BrandTags.net. One of those ideas you wished you had, BrandTags allows people to come in and partake in one of two activities. First, you are flashed a brand--like The North Face--and you type the first word or phrase that comes to mind. Tags are aggregated and presented in a cloud format. The second option is a forced trade-off for brands, ultra-simple style. So, you might have to choose between Microsoft and Apple. Is this biased? Of course it is!!! But, I bet it's a pretty good proxy for a digitally savvy 20- or 30-something male audience. Brands are also ranked against each other in a list, based on their "winning rate" in the head-to-head.

2. Buzz Monitor. Why the World Bank went and built their own tool to aggregate digital buzz I'll never know, but they did, and because they're .org they've made it available to anyone who wants to use it. All you need is a Linux server and the thing installs using Apache / MySQL / PHP. It basically goes out there and "scrapes" the web for what people are saying about you. Yes, it requires some effort, but it's very cool. I don't think it'll be free for much longer. I think they have non-profits in mind as users.

3. Nielsen BuzzMetrics / BlogPulse. It's no surprise that Nielsen's in this business, but this tool is pretty slick. Blogs are theoretically the "rawest" content on the web, and BlogPulse lets you see what's going on in real-time. There are free applications, but of course you have to pay for the good stuff. They have a neat blog that discusses some of the trends they're seeing in the blogosphere. This is mostly harmless stuff, yet good cocktail chatter. For example, the percentage of blogs mentioning "New Year's Resolutions" as the New Year approaches. Sometimes there are interesting posts for companies, such as this one tracking XBox vs. PS3 vs. Wii through the holidays. Turns out XBox is winning. Or, the interesting "bursty phrases" page which allows you to see which phrases are "accelerating" fastest out there. You can even do custom searches that are actually really enlightening. Say you wanted to do an informal analysis of the impact of Microsoft's Seinfeld commercials on the blogosphere. I did three searches and did a serial plot through six months.

This is obviously just the tip of the iceberg. It's astonishing how much a motivated marketer can learn about his brand, products, and customer perceptions by keeping a few sites bookmarked and checking periodically. The opportunity to do "big" market research tasks with little or no budget is huge, lowering barriers to entry for digitally-focused brands. I'm always on the lookout for new "listening" sites (beyond the obvious such as Google alerts) so keep the comments coming. Happy New Year... hope everyone had a great holiday season.

Using Customer Equity as a Dependent Variable for MarComm Optimization

I've written a lot about marketing optimization, ROMI, and mix optimization. In past posts, the dependent variables--the "things to optimize"--have been defined as time series variables of aggregated data. Some examples--"sales", "profits", "awareness." These would be entered into a model on a weekly or monthly basis, and then once a company has 70 or 100 of these data points, it can start building regression models to understand the effect of stimulus on response.

There are a lot of problems with this approach, particularly when trying to understand short- vs. long-term effects. A short term effect would be the impact of a demand gen campaign on sales. This would happen fairly quickly. A long-term effect would be attitudinal. As customers' perceptions of brand quality change, for example, this has a long-lasting effect that must be taken into account over many years. Decisions to spend money to affect perceptions of quality, though, must somehow be balanced next to decisions on how to spend money that will get customers in the door tomorrow. It's tough work.

Rust, Lemon and Zeithaml, in their 2004 Journal of Marketing Article "Return on Marketing: Using Customer Equity to Focus Marketing Strategy" have a neat solution. It's to make the dependent variable the customer. In other words, when making marketing investment decisions, companies should understand how each investment impact core "orthogonal perceptions" for each of its customer segments, and then trace the impact of these perceptions on customer behavior in the form of acquisition and retention. They suggest thinking of each customer relationship as a string of future actions--either they will or won't buy, at different amounts, through time. They do this using a mathematical technique called a Markov Chain.

So the approach that others recommend and I think can work really well for B2B marketers is to change the dependent variable from an aggregation to the atomic customers.

The nice thing about going investment-->perception-->customer behavior-->customer equity is that you have almost unlimited scenario flexibility. Because the atomic level data is at the customer level, you can change assumptions about segmentation easily and see the impact on ROMI. There are, however, a couple of key challenges:

1. How do we understand the impact of marketing investments on perceptions? The marketer still needs to do research, in the form of recognition tracking through time, to understand this.
2. How do we understand which core attitudes are truly important? Market research needs to be done, in the form of qualitative followed by quantitative research, to understand the constructs that truly drive acquisition and retention behavior. In the article, the authors tested questions on inertia, quality, price, convenience, ad awareness, information, corporate citizenship, community events, ethical standards, etc totally 17 questions. They used PCA (Principle Components Analysis) to whittle this list down to 11 constructs.
3. Customer segmentation. Not all customers act the same way, and the more discrimination we are able to build into our model, the better. Ideally, we'd like a unified segmentation to drive our research here.
4. True short-term goals. While this approach can theoretically handle all marketing activities, it doesn't describe how to handle true short-term actions. However, I think it's pretty easy to bolt this on. Because we're looking at customers as the dependent variable, we'd simply add on known short-term acquisition and retention levers to only impact the first step of the Markov Chain. If an email acquisition program drove 5% of a segment to but, we'd simply add 5% onto the first Markov chain probability.

There's a lot more detail to this, but it should give a taste to the marketer who's interested in using customer equity as a dependent variable for ROMI / mix modeling. If there's more interest, give me a shout, go to MarketBridge and register your name, or download the Journal of Marketing Article (or all three).

B2B CRM / Branding Model

I was doing some more thinking about a specific B2B CRM and branding model. This relates to a previous post on CRM. I was thinking about how you build an interaction model between the firm and its customers if those customers are businesses. I was also thinking about the function of "branding"--creating consistent communications across all customer touchpoints. A more holistic definition of branding might include all customer interactions, period, including services, products, even non-company-sponsored interactions such as through "key influencers."

The concept, while not earth-shattering, does provide some clarity to the role of branding and CRM in a B2B organization. It also leverages some of the concepts that I've been thinking more about lately, namely the core function of inbound marketing or listening and the imperative of thinking of the company-customer as a decision making unit and not just as a monolith.

Basically the framework divides up the CRM value chain into four parts. Let's stat with Marketing Management. This is the company function, and it is the marketing nerve center where all core decisions are made about the customers and the brand. The functions of marketing management involve product features, packaging, and value proposition; service elements, including all of the myriad post-sale touchpoints with customers; the marketing mix; and of course, segmentation, targeting and positioning.

The marketing management function's decisions are manifested in the outbound marketing function. Using a person as an analogy, this function amounts to "talking." The outbound function should entail communications (TV, radio, email, sales force, partners, etc.); experiences (product experiences; service experiences) and influentials (all of the sources that people listen to--the media, influential bloggers, influential user groups.)

The target of the outbound marketing are the business customers. These must be deconstructed from the firm to the decision making unit inside the firm to the individuals inside the decision making unit. Furthermore, individuals must be understood at the level of both behavior--what they do and attitudes and perceptions about the company and its products--which is of course THE BRAND. I can't emphasize enough how important it is to think of the B2B brand as the collective set of attitudes and perceptions latent in the individuals inside the decision making units at your firm's customers.

Finally, the fourth box is the inbound "listening" activity where your customers talk back to you. There are five primary elements of listening: sampling (tracking studies); chatter (web or otherwise); engagement (two-way conversations); purchase (buying); and loyalty (staying a customer). Generally, these five inbound vehicles paint a holistic view of the health of your company within a company, a DMU and key individuals inside the company.

I like this model because it brings together the core functions of both branding and CRM in a B2B context and provides a framework upon which to hang more complex ideas. It doesn't deal at all with technology (which is key to enabling both the outbound and inbound functions). It doesn't deal with any of the "technical" aspects of marketing, like PR, media mix optimization, etc., but it does allow slots for all of these things. Partner marketing could easily slot in to outbound and inbound, or you could actually build two business customer boxes for partners and end customers. In short, it's just a very versatile framework.

What Attitudes Drive Behavior?

One of my core beliefs about marketing is that ultimately people behave due to both immediate stimulus and core attitudes. Any purchase or defection decision is a function of a set of discrete events and of existing attitudes. To build a good model of customer behavior, it's necessary to describe both.

Attitudes are defined in psychology as a combination of "affect, cognition and behavior." Marketers commonly speak of attitudes like awareness, affinity or loyalty. Attitudes are mostly latent variables. Latent variables are not measurable by any conventional means. For example, I can't ask you how loyal you are to Company X and expect an accurate answer.

Fortunately, we can do market research that provides us good indicators of these latent attitudes. We can also look at other types of "in process" behavior that can describe these latent attitudes.

So which attitudes really do predict customer behavior? You can't really know until you start down a path of ongoing measurement, but here is a good list to start with:

• Loyalty
• Affinity
• Awareness
• Unaided Awareness
• Comprehension
• Recommendability

Of course, each of these attitudes needs to be measured accurately, and that's tricky. It takes a lot of thinking, a priori judgment, measurement, and subsequent refinement of the structure. However, once the structure is built, companies can begin to make much more strategic judgments about what marketing levers to pull when to get what effect. For those curious about how to start building a good attitude model for your company, I'd recommend looking at this article about factor analysis, which is a good way to understand how different metrics represent core customer attitudes, and this one on structrual equation modeling, which is a methodology for building a causal model.