How One Failure Turned Into A 10x Increase in Product Sales
As a self-professed data junkie, it is fascinating to watch the evolution of consumer-centric organizations’ use of data to offer increasingly personalized services to their users.
Think of YouTube’s recommended videos, Spotify’s ability to curate playlists for your weekend road trip, or Amazon’s uncanny ability to show you products you now want but never knew you needed.
The value of the YouTubes, Amazons and Spotifys of the world is that they inherently feel like ‘our’ product or service – something seemingly tailor-made, giving us a deeply personal, relevant, and quality experience on their platform. This, in turn, drives our lifetime value for each organization.
In speaking to industry experts, assessing client interviews, and culling through published research, it is clear that client expectations in the commercial sector are shifting to mirror this level of service that consumers have become so accustomed to in their personal lives.
Salesforce released an interesting study suggesting that 72% of businesses expect engagements that are personalized to their specific needs, while 67% have actually switched providers of a specific solution for a more ‘consumer-like’ experience.
Becoming more data-driven to give customers a personalized and valuable experience is something that most forward-thinking organizations aspire to - but it is often a challenge to go from ideation to actual implementation of this strategy, particularly in large, multi-faceted organizations.
I experienced this firsthand when I was tasked with leading a working group to deliver a sales tool for one of our US teams so that they could augment their more traditional approach and - in a broad sense - utilize our data more efficiently to proactively recommend solutions to our clients.
I viewed it as an exciting opportunity, and was confident that the solution I had envisioned would provide a tangible and measurable performance improvement to this particular team’s success.
But going from ideation to implementation is always tougher than expected.
Over the course of 12 months, and after meeting a half dozen technology experts (internal and external to my organization), we were no further along than we were when we first started our journey.
We were struggling to get access to the right data, challenged to dimension the problem in a tactical fashion, and hard pressed to secure adequate funding for what was, at the time, simply an idea on a piece of paper with no guarantee of success.
By all measures, I was failing to deliver on the vision I had promised to deliver.
A Turning Point: Realizing The Value of Simplicity
Something had to change – or else I was going to have to admit defeat by an endeavor I had dedicated myself to for over a year. Taking a big step back, I reassessed the situation at hand and realized that I needed to limit my initial scope.
I crafted a hyper-focused vision to deliver against wherein over the next 3 months, without going into the specifics, I was going to get access to a specific data set, mine it for trends, and use the data to proactively market offerings for a single product to clients.
This would be the most important part of the work we delivered, and was a big learning moment for me.
When dealing with a complex problem, there is immense value in taking a step back, redefining and limiting your scope, and approaching things simply.
Once I had limited the scope of the problem, I gained clarity and, with that, a renewed sense of determination. The overall task had become far more achievable.
Nevertheless, the three aforementioned components remained outstanding: (1) get the data, (2) mine the data, and (3) market what the data tells us to the relevant clients.
How would I overcome these challenges with dwindling interest and project fatigue, and without any real resources after the previous failure?
Reflecting on this make or break juncture - there were 3 lessons in particular that stood out to me as we began the process of turning this project around.
1. Don’t be afraid to get your hands dirty - no matter how far outside your official job description something may be.
Knowing that my biggest challenge would be to mine the data and build a model, and recognizing that I did not have a technology partner available to assist with this task, I proactively learned Python.
I enrolled in an online intensive course and spent my free time over the next 10 weeks learning and mastering advanced analytics and machine learning in Python.
In parallel, I worked with our product and reporting teams to trace the data necessary for this effort and identified 12 months worth of detailed data for me to leverage. This was labor intensive, and not a whole lot of fun - but had to be done.
I also hosted calls with our internal IT and Technology Architecture teams and advocated to have Python installed on my machine despite not being a developer.
Finally, I had all the bare bones needed to pull this off.
While still far from done, I was beginning to get excited - having rolled up my sleeves, I had made more progress in a few weeks than our previous efforts had made over the past year.
With all the tools necessary to build a model, I went into the office on a Saturday morning, plugged in my earphones, and had at it. I spent the better part of the day writing line after line of code.
By the end of the day, I had a preliminary model working.
By the end of the week, the model had been fine-tuned to the extent that I was confident in its results and ready for the next step.
2. The Difficulty Of Innovation Lies Not So Much In Developing New Ideas As In Escaping The Old Ones.
Despite having successfully built a model that we could use to proactively drive sales, I knew that there was a lot to prove to the team, so that they would risk moving forward from their more traditional approach to sales, and truly capitalize on the outputs of our recommendation engine.
To this end, I partnered closely with our marketing team and worked with them to generate excitement, to craft training material, to build marketing collateral, and to create a holistic pitch centered on a bespoke story for each client we were planning to approach.
We then identified a set of bankers and salespeople who we knew were looking for new ways to engage their clients - and adopted them as our pilot group. I worked very closely with these team members over the course of the next few weeks, attending client pitches together, debriefing on a regular basis, and iterating on our approach to perfect it for others.
3. Pitch Proven Success, Not High-level Concepts
After a few weeks of partnership with the pilot group, we began to capture enough feedback to prove preliminary success.
For every 2 clients we pitched to, 1 expressed interest in what we had to offer: a 50% conversion rate. While this may be skewed by the fact that we started our efforts with the strongest opportunities the model identified, it was still huge - especially considering that conversion rates for opportunities generated without this model, but for the same product, were yielding significantly lower conversions.
We began to build momentum – and needed to: given how large the opportunity was across the rest of the franchise, it was key that we scale beyond just the pilot group.
I put together a brief presentation of what we had completed, the success we had delivered, and began to socialize our achievements internally with other banking teams.
It is then that I realized something that may seem simple, but is critical learning: it is a lot easier to get buy-in on a proven model than on an idea.
As soon as I started pitching the success we had demonstrated in our pilot, bankers’ previous skepticism was all but gone, replaced by conviction and credibility in our use case.
Conclusion:
With the learnings of our pilot group in hand, we followed a similar approach with the wider audience and saw similarly successful results.
Clients were excited by our ability to proactively approach them with individualized suggestions to improve their businesses; bankers were thrilled to have a foot in the door for a warm conversation; and, after churning through hundreds of opportunities, we ended with an overall conversion rate 10 times higher than that we had touted previously.
It is abundantly clear that execution is the critical element that makes or breaks any idea.
Just because an idea fails to be executed through one avenue, doesn’t make the idea itself unworthy - a good idea should be pursued, it should be developed, and it should be executed.
There is huge value in taking a step back and dissecting the problem into bite-sized pieces, and tremendous merit in getting your hands dirty and doing all that is possible to get the job done.
To force people out of old habits to adopt new ones, success – perhaps generated through a pilot or proof of concept – must be demonstrated.
The journey to successful execution will of course vary from one project to another, but the principles stated above are fundamentals to any endeavor, and ones I will hold true to in each forthcoming effort: get your hands dirty, consciously shift from institutionally entrenched ideas of what has yielded success and lean into the otherwise unknown, and lead by demonstrated success rather than by high level concepts.
Leaders, after all, have three fundamental responsibilities: to craft a vision, to build alignment, and to champion execution.