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    The Conversation

    Case Studies

March 21, 2017

Does How Customers Identify Your Products Matter?

Dirt Devil has seven categories of products. Each of those categories has up to 28 different products within it. So it’s not enough to say, “You should buy a Dirt Devil.” That will only confuse the customer when they go to the website or march up and down the vacuum aisle looking for the recommendation. If there are dozens to choose from, how is the customer to know what’s best for her (or him)?

As Malcolm Gladwell so eloquently explained in a now famous TED talk, at one point in time, customers wanted choice. Diversifying it’s product offerings made Ragu a mint. Then there’s more recent examples about the paralysis of choice that indicates too many and customers will not buy anything.

We looked at some conversation research around the Dirt Devil brand and discovered that while we cannot pinpoint a correlation between too many choices and hard sales data in online conversations, we can observe how Dirt Devil customers refer to the products they use.

Dirt Devil Conversation Research - Products UsedWhile the categories led the way — indicating consumers are more apt to describe their Dirt Devil in broad form — there were several attempts at identifying specific product names and models. AccuCharge and SimpliStick were among the top six results of product identifiers in our research. That could speak to strong branding for those products. But why don’t others emerge? Does the brand divide its marketing among different agencies or marketing initiatives? Is that why some standout and others don’t?

Online conversations my not tell us the answers to those very specific questions, but a hearty conversation internally might.

And is it more beneficial to have everyone referring to Dirt Devil stick vacuums as such rather than in hodgepodge ways of reference? One hundred people shouting praise on a Dirt Devil stick vacuum is probably more beneficial than 24 complimenting the SimpliStick while 15 talk about the Power Stick and nine refer to the Power Air Stick, right?

This exercise is not to imply that Dirt Devil has a branding problem or unnecessary confusion among consumers about what products they offer. It is simply a way to open a dialog about the Paradox of Choice and whether or not branding initiatives could or should solve for it.

Word-of-Mouth Marketing is up to 200 times more effective than advertising, according to the Word-of-Mouth Marketing Association. Shouldn’t your brand’s conversation focus then be on unifying how people talk about you so you can deliver a more consistent wave of conversation when they do?

It’s certainly good food for thought and something you’ll never get a grip on unless you’re studying the online conversation about your brand. If you need help doing that, drop us a line. We’d love to help.

November 16, 2016

Understanding your audience with conversation research

There’s a spirits brand we’re familiar with at the Conversation Research Institute, not because they’re a client, but they’re a favorite for us when we break for a drink at the end of the week. Their marketing is not unlike other sprits brands in their category. It’s focused on tradition, heritage and quality. It’s aimed at men and of a particular status in life.

Honestly, you could take one of about two dozen brands in this category and put them in the same advertisements or even social media posts and, generally, the communications would work.

But we did some snooping around the conversation about the brand and found something interesting. The professions of the people who talk about the brand don’t exactly align with who the brand thinks they’re talking to.

Over the course of two months time, almost one fourth of the authors talking about the brand online listed themselves as artists. While certainly more research needs to be done to determine what type, what gender, how serious and the like, if you are targeting your messaging at male executives, does this data not give you pause?

Yes, 15 percent of the authors talking about the brand fall into the executive label. But the labels of “artist” “teacher” and even “journalist” add up to almost half of the online conversations about your brand, don’t you think segmenting and targeting them could result in more, bigger or better?

Conversation research isn’t just about finding sentiment and tone. It’s about uncovering insights about your brand that help you make critical marketing and business decisions. This particular brand of spirit is missing out on a huge content marketing or even targeting paid spend potential if they aren’t paying attention to the data that conversation research can unearth.

More can be had for your brand. Let us know if we can help.

November 1, 2016

Can Conversation Research tell you why sales are down?

 

A large national retailer in the food and beverage industry was riding high last year. Sales were up, the brand was healthy, consumers were immersed in the experience. Years of hard work had put the brand on the top of the heap in their category.

But then they noticed that sales of certain beverages had started flat lining. They couldn’t quite figure out why. Nothing in their formulas had changed. Customers weren’t indicating why they were switching drinks or passing on the drinks when they ordered. What was the brand to do?

They turned to online conversations and posed the question, “Are sales for these drinks flat lining because of a consumer shift or something else?” Consumers would likely tip their hand if it was the former. If the research was inconclusive, it wasn’t likely because of a consumer need, but something else.

The conversation research for the brand turned over an insight that explained it. The brand’s customers were becoming increasingly concerned about the sugar content of the drinks in question. They were interested in more healthy options.

So the brand formulated a new line of fruit-based, all-natural drinks just in time for spring.

The sugary drink sales stayed flat while the new line took off, exceeding expectations and satisfying customers.

So yes. Conversation research can tell you why sales are down. It may also tell you how to make them go the other direction.

Call us to see how conversation research can help your brand.

October 24, 2016

A peek inside Conversation Research around the travel industry

Understanding how conversation research data can help your business is certainly your first step in knowing what to ask for, who to ask it from and how you might approach discovering insights for your brand. There’s high-level data that points you in a general direction, then specific, granular research that can point to specific insights that help you make decisions.

I recently had the honor of sharing information about conversation research to the audience at TBEX, the world’s premier travel writing and blogging conference, in Manila, Philippines. In preparation for that talk, I recorded a little video to share some of the differences in high-level vs. specific insights with you. I also talk a bit about a specific example of a high-level insight that led to answers at a granular level.

So, what questions do you have about your business or industry that the consumer conversation may answer? I’d be happy to tell you as a response how conversation research may be able to help. Go ahead — the comments are yours!

October 4, 2016

The Achille’s Heel of Social Listening Software

If you use social listening software there’s a good chance you share a frustration with thousands just like you: You can never get the right data. Disambiguating online conversation searches is part Boolean Logic mastery, part linguistics and part voodoo. Or so it seems.

Disambiguation refers to weeding out all the data that comes back in your search query that isn’t relevant. It is a fundamental skill in the practice of conversation research. Type in the brand name “Square” for instance, and you’re going to have a hard time finding anything that talks about Square, the credit card processing app and hardware. Instead, you’ll find a sea of mentions of the word “square” including stories about Times Square, the square root of things and 1950s parents their children referred to as squares.

Disambiguation is a big problem for social listening platforms, yet most of them completely ignore the end user’s need for help. Some have build Boolean logic helpers in their software. Sysomos and Netbase have nice ones. But the only marketing professionals (who this type of software is targeted for) who understand Boolean logic switched majors in college.

What happens when someone who isn’t fluid in Boolean logic searches for conversation topics? You get a lot of results you aren’t interested in. And sadly, most end users of these software platforms don’t know any better. They see results, know they can output a couple charts or graphs for the monthly report and they’re done.

But the results they’re looking at are still littered with irrelevant posts. You can tweak your Boolean string all you want, but you’re likely to come up with something that looks right, but isn’t. And we haven’t even gotten to the Achille’s Heel yet!?!

Case in point: I did a recent brand search for a major consumer company last week. This was a simple brand benchmarking project where I was simply trying to identify all the conversations online that mentioned the brand, then decipher what major topics or themes emerged in those conversations.

My first return from the software was 21,000 conversations. As a reviewed them, I realized there was a lot of spam. After three hours of Boolean revisions, I narrowed the automatic results list to 1,654 conversations. But guess what? While they all were valid mentions of the brand, many of them were job board postings, stock analysis and retweets of news items mentioning the brand. None of these categories — which will likely show up in the automated searches for any sizable brand — are relevant to what the client asked of me: What are the topics of conversation when people talk about us?

So I manually scored the 1,654 conversations, creating categories and sub-categories myself. I also manually scored sentiment for any that made it to the “relevant” list. Here’s what I found:

  • 339 relevant conversations (* — Achille’s Heel coming)
  • 50% were negative; 32% positive and 18% were neutral (compared to the automated read of 92% neutral, 5% positive and 3% negative)

And here’s the Achille’s Heel: (Some topics redacted for client anonymity)

 

Despite manual scoring and categorizing, the majority of results I found were in a category I called “News Reaction.” These were almost all re-tweets of people reacting to a news article, which were removed in my automatic disambiguation process. The client doesn’t care about the news article (for this exercise) but for what consumers are saying.

The Achille’s Hell of Social Listening platforms is they generally do not automatically disambiguate your data well and even when you manually score it, there are reactions and by-products of original posts included that you don’t care about. (There are probably also ones not included that you do, but my guess is those are of less concern if your search terms are set well.)

This is the primary reason conversation research cannot be left to machines alone. For the platforms by themselves will make you believe something that isn’t actually true.

For more on how conversation research can help your brand or agency, give us a call or drop us a line.

 

 

Here’s where deep conversation research comes in. This is a topic chart for a major consumer company’s online conversations for a three month span

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