Selling is not the opposite of buying

Enterprise software is too big, too complicated, too complex for customers to know exactly what they’re getting. No matter how much we progress in making software observable, trialable, and easier to use, the scope of testing in exactly the customers’ environment is always limited.

CUSTOMERS BUY SOFTWARE, BUT THEY’RE SOLD PROMISES

Customers buy software, but they’re sold promises. Promises the vendor will advance the circumstances the customer seeks to accomplish.

When vendors harp on about the importance of presentation and professionalism, when we hear about the need for brand consistency, they’re talking about the promise. Everyone who talks to customers is part of the promise. All sales material is part of the promise. Every webinar, seminar, conference, and user summit are part of the promise.

If you put into words, what’s your promise to your customers?

Brand Conversations and Stock Performance

About a year ago, we comparatively visualized conversations between two competitive brands of major sport apparel companies.  The network of communications of Brand A showed better potential characteristics for healthy and robust interaction.

One year later, and more than 1,000,000 people talking about each brand, what do we see?

Brand A (one year later)

Brand A

Several million conversations later, we still see a deeply interconnected pattern of communication in Brand A.  The large number of clusters are still visible, but the interconnections are less clearly visible.  Let’s compare with Brand B:

Brand B

Brand B (one year later)

Brand B began with fewer, more centralized, clusters of conversation, and less “cross talk” between them.

Again, several million conversations later, it has evolved to a larger version of what we saw before.  While there are more distinct clusters one year later in Brand B than Brand A, each of those clusters receives less input from others.  Visually, we see this distinction by the are of fewer “clear” clusters toward center of the later graph of Brand A. In other words, should something great happen, the network of communications in Brand A would foster faster and more reinforcing communication.  If you’re a marketer, that’s what you want.

So, what’s the difference in stock performance over the past year?  Brand A outperformed B by about 30%.

Comparing Online Brand Conversations (Sports Apparel)

Over a long enough period of time, maps of who is talking with whom mostly look the same.  Many conversations start to overlap with each other, and eventually you see a large central core and any number of outliers.

However if you look over short enough periods, you can see patterns of how those conversations start to merge.  And, you can tell a lot.  Easily.

Brand A

Brand B

Here we have a mapping of conversation partners mentioning two of the top sports apparel manufacturers, measured over the same period. Compare the shapes of Brand A (on left) to Brand B.

Brand B (on right) has a few larger clusters of conversation, lightly linked together by a few individuals participating in a number of the conversations.

Brand A has a lot of smaller conversations, interspersed with a handful of larger dense clusters; all webbed together in wide mesh.

So which is better?

Continue reading “Comparing Online Brand Conversations (Sports Apparel)”

Election Influence by 527’s: Browsable Map

I wanted to put out what’s been done so far on making yesterday’s post more interactive. There’s an awful lot that could be better about this map. Particularly legibility of labels in the core (it’s just too dense). If you want to see names, I suggest looking at the edges of the map.

Michael Bommarito is looking into better layouts for legibility. And while you are waiting, I suggest getting your fill of everything he’s ever written.

The data was collected from OpenSecrets.org.

[21-Apr-2009: You should see a flash image above, but am having an awful time getting this to render on a Mac.  Works great on Linux (Red Hat Enterprise Linux).]

Demographics Fail

We forget, now that our reach is wide, that all purchasing is done by individuals.  Since we don’t know the individuals, and locating and selling to each and every one of them (us) is too expensive, we developed marketing to help us select the people, the individuals, most likely to purchase whatever we are selling.  We do that by carving up the population into demographic segments.  We do that by creating images and messages our testing tells us will appeal to those demographics.  As you noted, I am using the word “demographics” loosely – as it can just as easily mean single white 18-24 year-old men when selling video games, as it can mean general practitioners in the rural parts of beef exporting states when selling Lipitor.

759460300_63ca1caac9_mBut, why is this important?  Demographics provide us with statistically probable individuals.  Using these expected values are a great way for describing groups, but the value breaks down when talking about individuals.  We all know the story about the man who drowns crossing the river that is, on average, six inches deep.

The second failing in demographics is the pure focus on the individuals.  If the goal of sales and marketing is to convince individuals to take action (purchase, vote, visit, etc.), demographics alone does not provide the context under which we, as social animals, make decisions.

The number one factor that we as consumers use in making purchase decisions in consumer packaged goods, automotive, everything is our peers.  The younger we are, the better demographics reflect our peers, but that starts to break down rapidly once we leave school and enter the work force.

One place where we, as marketers, do a great job taking peer context into account is children’s toys.  Think about how they are advertised.  Is the latest and greatest StarBot 7000 action figure advertised with a static image of the figure with a voiceover talking about the high durability injection molded plastic construction and the die cast elbows capable of withstanding 30,000 hours of continuous play in -40°C conditions?  No, they show bunch of kids running around having a great time with the StarBot.  Children do not have long-standing deep networks of peers, so advertisers create a potential peer group in the advertisements.  Even as children get older, more media savvy, and create deeper relationships with their peers, all parents will recognize the plaintive cry of, “But, Billy has one!” Continue reading “Demographics Fail”

Sales Teams need Social Networks

Effective use of social networks (SN’s) is closer to sales than it is to marketing.  You want to build momentum in the network, and marketing alone will not provide that.

There’s a lot more to SN’s than better demographics, and given the abysmal value advertisers are are placing on Facebook (suggested $0.32 CPM vs. $1.15 for average online CPM in 2007 as per CPM Advisors LLC), demographics just aren’t cutting it.

Sealing the Deal
Sealing the Deal

The alternative SN’s should looking to is helping companies sell to their networks.  With all of the embedded relationship information, any salesman would love to get their hands on that data for companies they are selling to.

As SN’s age and continue to fill in, this becomes a reasonable opportunity (LinkedIn is already there).  In the meantime, SN’s have to provie value to retails scale vendors.  Since the per-sale return from using a sales team is likely to be negative, they need to place their bets on individuals likely to get others to buy too.

In other industries, we’ll use pharmaceuticals as our example, market research teams will do extensive survey work to determine the most influential figures in decision making relevant to their products.

Even after the enormous expense of conducting these 6 month or more research projects, and taking into account all of the known problems with determining influence with surveys, pharmaceutical companies often dedicate a specialized sales team to act on the data.  One company analyzed in a current paper showed approximately a 20% increase in revenue from this collaboration between marketing and sales.

Unfortunately, survey based methodologies become prohibitively expensive when moving from a 1,000 to 10,000 doctor network to a 10 or 100 million customer retail market.

The good news is, SN data is better and more accurate than surveys, and the data already exists.  You have the actual relationship matrix, rather than skewed survey information.  That alone provides quite a punch to sales.  Marry that with frequency of communication data, and you’ve got a goldmine for sales.

[Photo by: Beth and Christian]

Social Networks and Sales

This Guy Sells the Big Money!
This Guy Sells the Big Money!

From eponymous Social Network data alone, I can tell you who has, for any group, the most influence, who the leaders are, and who you need to convince in order to turn the opinion of the group as a whole. The question is are you going to be a trusted adviser, or a hard sell?

This ability to analyze a network often causes a knee-jerk reaction of unease by people new to the field, myself included when I first started. But, after considered thought and discussion, there are no new ethical questions here, just the same old difficult ones. First, a discussion of sales.

We all have friends whose opinions we trust above others about certain product classes. My brother-in-law is an incredible and studied amateur photographer (not that I can ever get him to update his gallery), and to him I turn for all things photographic. Another friend is an insatiable and articulate consumer of modern fiction, and whom feeds me many great book recommendations. For electronic gadgets, I turn to yet another. I trust their judgment and opinions; if you can convince them that your product is great, you have gone a long way toward convincing me. Further, switching to the general, we look to our gurus for information and ideas about the new. If you as a manufacturer/service/producer bring new ideas to my gurus, you are helping them seek out new information, which they tend to do naturally.

So, as a Social Network provider, or as a consumer of social network data for sales and advertising, you have a choice: treat networks as just another advertising platform, and be treated by the participants as just another advertiser; or provide value into the network, and reap the rewards.

[Photo by bonkedproducer]