Category Archives: Advertising

Why I’m Advising Bluecore

I first read The One to One Future by Don Peppers and Martha Rogers in 1997, four years after it was published.  As a marketer, the book made a big impression on me.  It was revolutionary stuff:  we should make the paradigm shift from mass marketing to individualized marketing.

When the book was published in 1993, newspaper ads were $75B/year, TV around $60B, the web browser was a mere three years old, and there were 623 total sites on the web.  There was effectively no web advertising market.  It was nine years before the Minority Report popularized a future vision of one-to-one advertising.  It was six years before Paco Underhill published Why We Buy revealing insights gleaned by manually tracking shoppers to understand in-store behavior [1].

Look at the subtitle: “Building Relationships One Customer at a Time.” You could use that in a webinar today.  The One to One Future was not just ahead of its time; it was so far ahead of its time that it could have equally been categorized under either “marketing” or “science fiction.”

Why?

  • It turns out, as with science fiction, that it’s easier to envision something than to build it. Remember, “they promised us flying cars and we got 140 characters.” [2]
  • Building individualized marketing systems required layers and layers of underpinnings that were simply not in place. You can’t do good personalization without a clean, real-time, 360-degree view of your customer.  Clean means a big effort into data quality and data profiling and typically either master data management or a customer data platform [3].  Real-time means real-time data integration [4].  360-degrees means pulling relevant data from virtually all of your systems.  Self-driving cars don’t work on cow paths.  Building those layers of requisite infrastructure has taken decades.
  • Marketing’s focus on the perfect offer was flawed. Say I found an offer with an 90% chance that you’d respond affirmatively.  Perfect, right?  But it was for a product that was out of stock.  The perfect offer has to be for the right product, in the customer’s preferred size or color, and available to sell.  We can’t just find the set called {great offers}.  We needed to intersect it with the set called {in stock and need to sell}.  This made a hard problem harder by pulling inventory and the supply chain into the equation.
  • Marketers got trapped in a vicious downward cycle of communications. Email click rates have nearly been cut in half over the past decade.  Marketing’s solution?  Send more emails to make up the difference.  Email vendors, who typically price by the email, were only too happy to accommodate.  That, however, is a short-term mentality.  More bad email with lower open and click rates isn’t the solution.  The same holds for ads and promotions.  Marketing needs to get out of this race to the bottom.  We need to focus on quality, not quantity.  And pay vendors for performance delivered, not communications sent, while we’re at it.
  • Finally, the retail industry needed to shift mentality from store-first to digital-first. Roots, as they say, run deep and retailers have long, deep roots in physical stores.  Bricks-and-mortar supposedly changed to clicks-and-mortar, but really, it was mortar-and-clicks the whole time.  The industry never really changed to digital-first from store-first.  Until Covid-19, that is.  While this meme, popularized in Forbes, was intended for many industries, it could have been custom made for retail [5].

So where does Bluecore fit in?

  • Bluecore is a multi-channel personalization platform. They’re building what marketers in the past dreamed of, but couldn’t build, because the infrastructure wasn’t there.  Now it can be built, and they’re building it.
  • Bluecore is an AI/ML company focused on retail analytics and personalization. I’ve blogged before that AI/ML is best applied to specific problems and not general ones, and this is a great example.  They are a closed-loop, retailed-focused application that gets smarter every day and with each new customer.  If you believed in the increasing returns of marketing leadership in technology markets before AI/ML [6], you should believe in them twice as much after.
  • Bluecore’s personalization understands both customer and product – and intersects them. Across a catalog of more than 250M products and SKUs, Bluecore can match customers and products at a 1-1 level.  It automates what would have been the work of a team of in-house data scientists.
  • Bluecore is paid for performance, not volume. They back up their performance claims with a pricing model based not on volume but on success.  This is a great example of superior technology enabling disruptive business model innovation.

Why am I advising Bluecore?  Three reasons:

  • As a true, blue marketer this stuff genuinely interests me. I love working with marketing companies on marketing problems.
  • It’s always about the team. I’ve loved working with Fayez Mohamood (founder/CEO) and Sherene Hilal (SVP of Marketing).  As a bonus, former Salesforce teammate Scott Beechuk is an investor and on the board.  I like working with people who like working with me and appreciate my inimitable (I inadvertently almost typed inimical) style when it comes to feedback.
  • The momentum and market opportunity. Bluecore’s a highly successful company, having raised over $100M in VC with top-tier investors, and they are pursuing transformational change in a $4T market.  The last 100 years in retail were all about stores, the next 100 will be about retailers meeting customers wherever they are.  And that’s what Bluecore does.

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Notes
[1] And why, to this day, you can find still baskets strewn throughout many retail shops as opposed to only at the entrance.  His work was kind of a manual predecessor to systems like RetailNext, whose founder I got to know through mutual investments in a prior life from StarVest.

[2]  Peter Thiel at Yale.

[3] Which weren’t to be invented for about 20 years

[4] The data warehouse was invented in 1992, with the publication of Bill Inmon’s Building the Data Warehouse.   Ralph Kimball would invent the star schema 4 years after that.

[5] Apologies to frequent readers for using this meme again – but I just love it!

[6] Tech buyers, and particularly IT buyers, tend to face high opportunity costs and high switching costs and are ergo generally risk averse.  This drives increasing returns for early market leaders.  Think:  no one ever got fired for buying IBM.

The Key to Branding Success: Staying in Character

Decades ago I had the pleasure of watching a branding video, created by a San Francisco ad agency, narrated by an advertising executive with a familiar voice who’d narrated scores of commercials [1].  It was, I believe, entitled Staying in Character and while I’ve searched the internet for it many times over the years — and just spent another hour unsuccessfully trying again — I’ve never managed to find it.

The video talked about the importance of brands staying in character in their marketing and advertising.  Sadly, nowadays, when you search for “brands staying in character,” you’re more likely to come up with an article about mascots than one about brand character.

All these thoughts were stirred up the other morning when I read this story about Hugh Grant.

Staying in Character used actors as one example, arguing that most actors’ worst movies are when they were (as the Hollywood expression goes) playing against type, such as John Wayne as a Roman centurion, Sylvester Stallone in Stop! Or My Mom Will Shoot, or Macaulay Culkin playing a psychopathic murderer.  While defying type entirely, or successfully playing against it, is undoubtedly a great accomplishment for an actor, most audiences don’t like it.

We want John Wayne as the tough lawman, Sylvester Stallone as Rocky Balboa, and the Home Alone kid as the Home Alone kid.   We want actors playing in type, not against it.

It’s a straight conflict of interest between the actor/product and the audience/consumer.  Hugh Grant wants to show the world that he can play a role other than the romantic Englishman.  However, just as we want our coffees customized at Starbucks and the restrooms clean at McDonald’s, we want Hugh Grant to be a romantic Englishman.  We don’t care if Hugh Grant is bored of being Hugh Grant.  That’s his problem.

Musicians have the same challenge.  They get tired of playing the same old songs and want to play their newer material, but the fans want to hear the classics [2].  James Taylor, ever humorous, put this well in discussing his hit cover of You’ve Got a Friend.

Taylor described the night he first heard songwriter Carole King perform the song. Taylor got so excited that, he said, “I literally ran to get my guitar and try to learn how to play it. Of course, I didn’t realize then I’d be playing it every night for the rest of my life.”

The other example I remember from the video was a discussion of Jack Daniels, who’s been credited with creating one of the longest-running advertising campaigns in history.  Here are two of their ads from the 1980s.

That’s branding.  It starts with the product and the packaging.  But it’s also as much about who you are as how you talk.  (By the way, isn’t that copywriting delightful?)

While storytelling is all the current marketing rage, and while these ads certainly tell stories, staying in character goes beyond the telling of individual stories to how you link numerous brand-building stories together over time.

Really, it’s about one thing:  consistency.

  • Defining who you are (your essence) and how you talk (your voice)
  • Consistently communicating your essence in your voice — always, never playing against type
  • Sticking with that come hell, high water, or — much more dangerously — a new CMO

It’s about you being you.  Or, for that matter, Hugh being Hugh.  And it’s why:

In the end, it’s about defining who you are, communicating it, and sticking with it.  That’s staying in character.  And it’s critical to any branding effort.

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Notes

[1] Yesterday’s guess was Hal Riney, but I don’t think it was him.  The voice was too warm and not nasal enough.

[2] Even the Grateful Dead, despite their improvisational style, deep repertoire, and ever-changing setlists, fell subtly victim to the “what we want to play” vs. “what they want to hear” phenomenon.

Marketing Targeting: It’s Not Just Where You Fish, It’s What You Put on the Hook

Back in the day I was taught that marketers do three things, memorized via the acronym STP:  segment, target, position.

  • Divide the audience into different segments.  For example, dividing consumers by demographics or dividing businesses by size or industry.
  • Select the segments that the company wishes to target for its marketing.  For example, choosing small and medium businesses (SMB) as your target segment.
  • Position the product in the mind of the consumer, ideally in a unique way, providing differentiation and/or benefit [1].  For example, positioning your offering for the SMB segment as easy to deploy and inexpensive to own.

I’ve always thought of targeting as the answer to the question, “what list do I want to buy?”  Do I want buy a list of marketing directors at SMBs or a list of chief data officers (CDOs) at Fortune 1000 companies?

The list-buying metaphor extends nicely to events (what shows do these people attend), PR (what publications do they read), AR (to which influencers do they listen), some forms of digital advertising (e.g., LinkedIn where you have considerable targeting control), if not Google (where you don’t [2]).

For many people, that’s where the targeting discussion ends.  When most people think of targeting they think of where on the lake they want to fish.

While an angler would never forget this, marketers too often miss that what you put on the hook matters, too.  Fishing in the same part of the lake, an angler might put on crayfish for largemouth bass, worms for rainbow trout, or stinkbait for catfish.

It’s not just about who you’re speaking to; it’s about what you tell them — the bait, if you will, that you put on the hook.

Perhaps this is too metaphorical, so let’s take an example — imagine we sell financial planning and budgeting software to businesses and our target segment is small businesses between $0M to $50M in revenue.  Via some marketing channels we can communicate only to people in this segment, but through a lot of other important channels (e.g., Google Ads, SEO, content marketing), we cannot.  So we need to rely not only on our targeting, but our message, to control who we bring into the lead funnel.

Consider these two messages:

  • Plan faster and more efficiently with OurTool
  • End the misery and mistakes of planning on Excel

The first message pitches a generic benefit of a planning system and is likely to attract many different types of fish.  The second message specifically addresses the pains of planning on Excel.  Who plans on Excel?  Well, smaller businesses primarily [3].  So the message itself helps us filter for the kind of companies we want to attract.

Now, let’s pretend we’re targeting large enterprises, instead.  Consider these two messages.

  • End the misery and mistakes of planning on Excel
  • Integrate your sales and financial planning

The first message, as discussed above, is going to catch a lot of small fish.  The second message is about a problem that only larger organizations face — small companies are just trying to get a budget done, whereas larger ones are trying to get a more holistic view.  The second message far better attracts the enterprise target that you want.  As would, for example, a message about the pain and expense of budgeting on Hyperion.

I’ll close in noting that marketers who measure themselves by the number of fish they catch [4] — as opposed to the conversion of those fish into customers — will often resist the more focused message because you won’t set attendance records with the more selective bait.  So, as you perform your targeting, always remember three things:

  1. It’s about where you put the boat
  2. It’s also about the bait you put on the hook
  3. It’s not about the number of fish you catch, but the number of the right fish that you catch.

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Notes

[1] The decision to emphasize differentiation or benefit is covered in The Two Archetypal Marketing Messages:  “Bags Fly Free” and “Soup is Good Food.”

[2] In a B2B sense, at least.

[3] Amazingly, a lot of large and very large businesses also plan on Excel, but let’s not confuse the exception for the rule or the point of the example — different messages attract different buyers.

[4] Either literally by putting KPIs on high-funnel metrics such as MQLs or, more subtly and more dangerously, by getting too much inner joy from high-funnel metrics (“look how many people came to our webinar!”)

The Dogshit Bar: A Memorable Market Research Concept

I can’t tell you the number of times I’ve seen market research that suffers from one key problem.  It goes something like this:

  • What do you think of PRODUCT’s user interface?
  • Do you think PRODUCT should be part of suite or a standalone module?
  • Is the value of PRODUCT best measured per-user or per-bite?
  • Is the PRODUCT’s functionality best delivered as a native application or via a browser?
  • Would you like PRODUCT priced per-user or per-consumption?
  • Rank the importance of features 1-4 in PRODUCT?

The problem is, of course, that you’ve never asked the one question that actually matters — would you buy this product — and are pre-supposing the need for the product and that someone would pay something to fulfill that need.

So try this:  substitute “Dogshit Bar” (i.e., a candy bar made of dog shit) for every instance of PRODUCT in one of your market research surveys and see what happens.  Very quickly, you’ll realize that you’re asking questions equivalent to:

  • Should the Dogshit Bar be delivered in a paper or plastic wrapper?
  • Would you prefer to buy the Dogshit Bar in a 3, 6, or 9 oz size?
  • Should the Dogshit Bar be priced by ounce or some other metric?

So before drilling into all the details that product management can obsess over, step back, and ask some fundamental questions first.

  • Does the product solve a problem faced by your organization?
  • How high a priority is that problem?  (Perhaps ranked against a list of high-level priorities for the buyer.  It’s not enough that it solves a problem, it needs to solve an important problem.)
  • What would be the economic value of solving that problem?  (That is, how much value can this product provide.)
  • Would you be willing to pay for it and, if so, how much?  (Which starts to factor in not just  value but the relative cost of alternative solutions.)

So why do people make this mistake?

I believe there’s some feeling that it’s heretical to ask the basic questions about the startup’s core product or the big company’s new strategic initiatiave that the execs dreamed up at an offsite.  While the execs can dream up new product ideas all day long, there’s one thing they can’t do:  force people to buy them.

That’s why you need to ask the most basic, fundamental questions in market research first, before proceeding on to analyzing packaging, interface, feature trade-offs, platforms, etc.  You can generate lots of data to go analyze about whether people prefer paper or plastic packaging or the 3, 6, or 9 ounce size.  But none of it will matter.  Because no one’s going to buy a Dogshit Bar.

Now, before wrapping this up, we need to be careful of the Bradley Effect in market research, an important phenomenom in live research (as opposed to anonymous polls) and one of several reasons why pollsters generally called Trump vs. Clinton incorrectly in the 2016 Presidential election.

I’ll apply the Bradley Effect to product research as follows:  while there are certain exception categories where people will say they won’t buy something that they will (e.g., pornography), in general:

  • If someone says they won’t buy something, then they won’t
  • If someone says they will buy something, then they might

Why?  Perhaps they’re trying to be nice.  Perhaps they do see some value, but just not enough.  Perhaps there is a social stigma associated with saying no.

I first learned about this phenomenom reading Ogivly on Advertising, a classic marketing text by the father of advertising David Ogilvy.  Early in his career Ogilvy got lucky and learned an important lesson.  While working for George Gallup he was assigned to do polling about a movie entitled Abe Lincoln in Illinois.  While the research determined the movie was going to be a roaring success, the film ended up a flop.  Why?  The participants lied.  After all, who wants to sound unpatriotic and tell a pollster that you won’t go see a movie about Abe Lincoln?  Here’s a picture of Ogilvy doing that research.  Always remember it.

ogilvy

Too Much Money Makes You Stupid — Let’s Make an Alec Baldwin Viral Video

There are two sayings I like when it comes to the unicorn bubble:

  • “Too much money makes you stupid”
  • “Any idea’s a good one when you’ve got $100M burning a hole in your pocket.”

Startups are supposed to be focused.  Startups are supposed to need to prioritize ideas and opportunities.  Just as startups weren’t supposed to buy Superbowl ads, startups aren’t supposed to have hundreds of millions of dollars to plow through in the name of creating brand mystique either via huge-budget events like Domo’s Domopalooza or would-be viral videos, like the one below.

But wait, you protest, didn’t Salesforce always do aggressive marketing and wasn’t that risk-taking part of their greatness?  Well, yes and no.  A good part of their early marketing was guerrilla PR done on the cheap.  Yes, they also ran big events, but they mostly found a way to pay for them — Salesforce raised $53M in VC before going public.  Domo has raised nearly 10x that.

Now, I have no particular beef with Domo. Other than being next-generation BI, I must admit to always having had some trouble figuring out what they do — in part due to the abnormal secrecy they had in their early days.  I know they don’t compete with Host Analytics so I have no beef there.  I also know they have sexed-up the BI category a bit, and they’ve certainly done a great job of positioning themselves as a cool company and have created a lot of buzz in the market.

But at what cost?

Domo has raised $483M.  It does cause one to wonder about their capital-to-ARR ratio, which is a great overall capital efficiency metric and one that no ever seems to talk about.

  • While I don’t know in Domo’s case, I’d guess for many unicorns that this ratio is 10 to 20x — where the company is running a kind of perpetual motion machine strategy where you generate the Halo Effects hoping to drive the sales that justify the valuation that you got on your last financing.  This strategy, as many will discover, works well until it doesn’t.  If the epitaph of Bubble 1.0 was about Network Effects, that of Bubble 2.0 will be about Halo Effects.  Remember Warren Buffet’s famous quote:  “only when the tide goes out can you see who’s swimming naked.”
  • I know for a reasonably capital-efficient SaaS business the capital-to-ARR ratio might be 2-3x.  Perhaps an order of magnitude difference.

Back to our core topic — what’s an example of something that looks like a good idea when you have $483M burning a hole in your pocket that, well, might not look like such a good idea if you were forced to lead a more frugal marketing existence?

How about  a YouTube mini-series with Alec Baldwin?  That’s exactly what Domo did.

Here’s episode 1 about “rancid data” which, among several issues, breaks the fundamental rules about how to make a successful viral video.

The Big Cheese: Velveeta Network Marketing with House Party

I caught a Facebook status update from childhood friend and neighbor, Gene DeRose (who, among other things, founded Jupiter Communications), which linked to a Wall Street Journal article about his new company, HouseParty, and the big Velveeta House Party that they are running on Super Bowl Sunday.

Always interested in marketing, this got me asking: what’s a House Party? The answer: a modern-day, high-tech interpretation of the old Tupperware party.

From their site:

Is a House Party like a Tupperware party?

Yes… and no. There are many appropriate analogies to be made to the successful phenomenon that is a Tupperware party, but a House Party is different in one key way: hosts of house parties are not paid representatives of any of the products that are showcased at the event.

Instead, a House Party host is typically a brand ambassador – a consumer that already has a positive association with the brand(s), and who is likely already out doing something we simply want them to do more of: telling their friends about the brand. House Party finds the most viral of these consumers, and gives them ways and reasons to do more of this advocacy while also allowing us to guide and sculpt some of it, peek in on how it’s going, and track it.

I suspect there’s some cool data mining technology involved, because they somehow identify the “most viral” of the House Party applicants. For example, for The Big Cheese, only 2,500 of the 15,000 applicants were selected.

Good luck with the concept Gene and Parker: it seems like a good one.