Marketing acts like a giant pendulum.
What worked a year ago may not work today. What’s working today may no longer work a year from now. In the era of SaaS and digital products, opportunities get saturated, best practices become overused, everything suddenly becomes highly measurable, more predictable, and over optimized. Things that we relied on become less effective over time and its efficiency fades out.
Everything in marketing is doomed by this rule. Continue reading
By now, you’ve probably already seen this image from Scott Brinker.
It gives you a realistic idea of how rapidly the marketing and sales technology landscape has evolved over the last 5 years and how tough the competition has become.
Every product that is able to affect the customer’s experience is — in some way competing.
However, as marketing technology’s power and ubiquity have grown, its strategic importance has not diminished. Modern marketing teams – more than ever – find their sweet spot on the boundaries between the technology domain populated by algorithms, systems, data, and the human domain populated by creativity, psychology, and brand.
Lately, I’ve been wondering how much of this marketing technology wave are customer ops teams really exploiting? In what proportion do they really use this new abundance of SaaS? And what is the speed of adoption of these new technologies?
While growth in marketing technology follows an exponential curve, organizational changes happen on a logarithmic curve.
This essay is a deep dive into the causes that hinder most companies from fully exploiting today’s technology abundance and the approaches that might solve some of today’s problems.
Sometimes marketers trick themselves and fall in love odd definitions. You’ve probably heard that “help is the new selling,” as if it’s something new. But is it, really? Isn’t this what salespeople have been doing since … ever? Isn’t “helping people” at the core of selling? In thinking about this, I’ve had a chance to think about how the role of sales is changing.
Something has changed and it’s continuously evolving over time, only it’s not the helping per se. What has changed is how salespeople help.
At this year’s SaaStock conference, I had the opportunity to talk with a lot of amazing people (founders of SaaS-oriented companies, marketers, salespeople, C-levels). Many of them thought that I was in marketing or that I previously worked for a marketing services company or similar.
Instead, my path couldn’t be more different. I’m a technical guy who has spent his career in the IT world. I founded my first IT company when I was 17. I spent the next 13 years building reliable IT infrastructures and web apps. I had the opportunity to see a startup grow from 3 to 60+ employees. I also lived the exciting experience of joining the 500 Startups family in 2014 (batch 11).
I credit these experiences for helping me understand the walls that tend to separate Marketing, Sales, Product/Engineering, and Customer Service from one another. More importantly, they also show me how we can tear them down.
I’ve recently come across a number of articles that claim that “customer experience is the new marketing.”
After reading those words over and over again, a little idea started to whirl ‘round in my head.
I am a firm believer that good marketing focuses on what the potential user already wants to do, not on something that you want them to do. With this in mind, how is this “customer experience” idea something new?
Well, in fact, it’s not new at all.
Customer experience is actually the old marketing. “Old” not because it’s no longer cool but because it’s at the core of fundamental marketing practices. Retail and consumer marketing introjected this idea, not yesterday, but years ago.
All metrics are shortcuts. When we’re faced with uncertainty, we use metrics to break our problem down into simpler, tangible pieces that we can understand.
Metrics are simple proxies that allow us to transform difficult questions into empirical, demonstrable ones.
When we’re faced with a difficult question, we often answer an easier one instead, usually without even noticing this subtle substitution. This is what economists call an availability heuristic — a mental shortcut where we use what we already know, rather than complete information, when making a decision.
A few weeks ago Hiten Shah explained in a new interesting post why the most successful SaaS companies of the future will focus on usage, just like Facebook. In the write-up, he goes very deep into his explanation bringing examples of world-class SaaS companies like Trello, Slack, and Dropbox that are all building their strategies around this consumer-oriented product approach.
He predicts that this is how the next generation of SaaS will look like.
While I was reading Hiten’s post, I immediately recalled a frugal email conversation I had last month with Patrick Campbell, CEO at Price Intelligently.
Patrick briefly introduced me to the definition of what he calls “anti-active usage” products.
Building a marketing strategy from the ground up isn’t easy, especially when the product you’re supposed to be selling is still being developed. Here at RepIQ, we knew we wanted to launch and scale quickly, so it was important for us to leverage our time pre-launch to develop an effective marketing strategy. We utilized weekly marketing experiments to quickly test various tactics and determine which would be most effective.
This experimentation process helped up attract 1,000 users pre-launch and also helped us develop a scalable marketing strategy. And while we tested dozens of tactics that didn’t work, we also discovered some clear winners. From our marketing-experiment methodology, to the effective tactics we (eventually) figured out, to best practices for implementing these tactics, I’ll be covering all that and more in this post.
At the beginning of every startup, the most helpful data usually isn’t quantitative; it’s qualitative. You can’t measure very much in the early days for the simple reason you just don’t have enough data.
Analytics products like Google Analytics, Hotjar or Mixpanel won’t help you understand what problems your users really need to solve or what features you should prioritize after launch. At this stage, the only way for you to have a reasonable perception of the needs and the trends is to go out of the office and talk to people.
But when companies start to grow, they rapidly orient from a qualitative to a quantitive data collection approach. Which means they quickly start paying more attention to statistically significant numerical data than descriptive data, usually harder to analyze.