I Wrote An Email To Jeff Bezos Years Ago With A Proposal: Here’s How He Responded
Some years back, I took the bold step of sending an email directly to Amazon’s, soon-to-be-former-CEO, Jeff Bezos.
Somewhere I’d located his CEO hotline address. Reputedly, he promised to personally answer each query.
In any case, reaching out to top decision-makers in such a way was something I’d become accustomed to. I’m an independent consultant, and I’ve learned over the years that if you want to make it rain, you need start at the top of the mountain.
After all, the worst anyone can do is ignore you.
But in Bezos’s case, he didn’t.
On the contrary: the response I received was instructive and it taught me several lessons about how innovators should or should not pitch themselves and their ideas to giant companies.
But before I get into what I requested of him and the response I received, let me give you some background…
The Backstory
About 10 years ago, I led a data science team in creating one of the world’s first mobile-payments and -lending eco-systems. I’m an American, but this eco-system was for a bank I was working for in Kenya as a senior executive and board member.
The relevance of my positions was that I was privy to and part of the actual strategy-formation of the bank.
Long before my time, the bank had invented the now famous, mobile payments system dubbed, “Mobile-Money”. Furthermore, a former partner-turned-competitor of the bank (a telecom) shaped Mobile Money into an iconic product called, “M-PESA”.
My job was to help the bank take its own version of Mobile Money to the next level — lending. In particular, my team was to create a suite of pre-approved and instantaneous lending products that people could apply for and use solely from their mobile phones.
Looked at now, 10 years later, what we were doing seems almost commonplace. However, at the time it was pretty cool. This was partly because my (all-African) team was brilliant and we had an open book to use whatever data science methods and technologies we needed to get the job done.
With permission from existing customers, for example, we scraped Twitter accounts using Natural Language Processing (NLP). We then coupled that information using what I now call, ‘behavioral data science’. Our aim was to design the lending products in line with the needs we detected from our customers’s social media conversations.
For example, we looked for phrases and words in Tweets such as “mom’s house,” “furniture,” “rent” or “my fiancee”. And using this information and behavioral data from the accounts, we created loans for purchasing appliances and furniture, paying school tuition and marriage dowries.
In fact, I take back what I said earlier: What we were doing is STILL pretty cool!
It was also profitable and beneficial to customers.
Even before we reached the end of the creation cycle, for example, the products were wildly successful. In other words, we’d found a way to create products that differed substantially from traditional bank offerings (i.e., credit cards, mortgages, etc.) while creating benefits on both sides.
The Email to Bezos
Some time after leaving my position with the bank in Kenya, I began consulting for some gigantic banks in China. In general, I advised them on innovating their mobile lending and digital transformations along with strategic investments.
Their aim was to fend off disruption from social media giants, like Alibaba and Tencent. These activities were the core part of their strategy.
In fact, early on, I remember a conversation with one client that made me realize I’d changed leagues. They told me their early attempts at creating mobile-based loans were “unsuccessful” because, in one year, they’d only gotten 16 million customers to respond.
When I said, “That’s great!” They said, “No, WeChat got 100 million.”
I realized I needed to up my game. Among other things, it meant incorporating newer technologies into the ecosystem architecture, such as AI and deep learning. We also explored new applications, so as AI for wealth management.
By November of 2017, I’d become confident that such a mobile ecosystem could also work in the US. That’s when I reached out to Bezos.
I’d seen how the platform worked in two very different markets — one smaller, one much larger — and felt Amazon was the perfect giant to work with.
In particular, I approached Mr. Bezos with the angle of “banking the unbanked”, which I’ll explain in more detail below. Let’s first look at the email (the hotline said to call him, “Jeff”):
Dear Jeff,
“I’ve no idea whether this email will ever get to you, but if it does, I hope it will be worth your while reading it…[Blah, blah, blah, about me and the lending eco-system…] My hope is to interest you in collaborating to bank the unbanked in the US and elsewhere, by helping your product and data science teams in designing and underwriting similar, financial products….
[Here’s where it gets super thick…]
I simply think it would be both exciting and fun to help Amazon — a company I greatly admire — create something much bigger and much cooler than the world has ever seen…”
[‘Help Amazon’? What was I thinking? Completely audacious, presumptuous and self-congratulatory, but hey, I was a bit younger then and had to sell!]
At the end of my email, I did the usual closing. I also linked an example of the significance of our work and how it might work with Amazon’s apparent strategy.
But before discussing the response I received, let me say a few words about why I was so audacious, presumptuous and enthusiastic…
‘Banking The Unbanked’
At the time I was working in Kenya, the country was more mobile- and Twitter-penetrated than both China and the US.
Around 70 percent of Kenyans were using mobile phones daily, while over 90 percent of internet users were using Twitter. Most Kenyans were accessing the internet using mobile phones--so this was a nested, digital environment.
The reason for the high mobile penetration was structural. Poor physical infrastructure in the country necessitated that people on mobile-telephony. This was their means for both communicating and for making financial transactions.
Moreover, M-PESA was the biggest Mobile Money product out there. By 2008, almost all of Kenya’s mobile-adept, population was using M-PESA. This was several years before Apple Pay (2014) or Google Pay (2015) came into existence.
In fact, at one point, Google even sent a team to observe how we were doing at the bank. The encounter resulted in their later creating “Google (Bebapay) Card” under joint venture.
The point is that Kenya was an ideal environmeny for us to learn how to innovate for the sake of solving real problems.
Those problems not only involved sending and receiving money. They involved obtaining emergency funds and undertaking long-term, financial planning planning. Indeed, our products were aimed, specifically, at enabling people to smooth their day-to-day, economic ups and downs.
This turned out to be a life and death matter for many, especially when interest rates or inflation spiked.
For example, as an American, I was ignorant of the extent to which currency fluctuations and spikes in electricity and even cooking oil prices could impact peoples's survival. To learn exactly to what extent, I designed a tool my team affectionately called, “The Majority Market Index” (MMI) — so-dubbed, because the majority of our customers were poor.
Here’s a simplified example that showcases my poor graphics abilities:
Using a month-ahead forecast, the MMI measured the anticipated market prices of a basket of survival fundamentals for most Kenyans (e.g., cooking oil, electricity, transportation fees, the blue line). This changing index number was compared to the average subsistence income of poor Kenyans (the red line), which stayed relatively constant over a year.
And there was a bit more to it. We wanted data on the real things Kenyans buy. So my team and started going to open markets in the poorest, but most densely populated, areas. We’d take photos of prices, which changed daily. Other forecasted prices for electricity, gas and oil we’d obtain from official data.
(While this seems specific to Kenya, almost any country I’ve traveled has “local prices”. Thus, if one is in LA, it’s doubtful a check cashing station or a barber shop in an ethnically concentrated neighborhood will have prices published on the internet.)
Interpreting the MMI gave us a way for developing a product strategy.
We reckoned that whenever the blue line was above the red line — i.e., whenever the average costs of living exceeded average means of living — our customers were hurting and needed loans. That triggered loan offers through text messages from the ecosystem.
Conversely, whenever the costs of living were anticipated to fall below means, we offered savings account options at high rates of interest. The latter offering was designed to giving customers a chance to recoup money lost from inflation.
Unfortunately, this latter, savings aspect of the system was never developed during my tenure at the bank.
Mixed with providing payments, it’s not hard to see how this ecosystem would help customers plan their monthly spending and saving. Knowing that prices might rise in the next month, for example, enabled a person to borrow temporarily to pay school tuition for their children, while spending their cash on subsistence needs.
I should also note that, unlike most banks, our products had extremely low interest rates relative to the markets (almost at cost). The reason was behavioral but also social. Kenyan customers were more amenable to paying fees for each service as opposed to interest. We were also not open to charging exorbitant interest rates to poor people.
Using this approach, fees could be set to be set to levels less than what customers would spend in accessing traditional services (say, through car or bus) but high enough for us to profit.
This was a win-win reduction in the deadweight loss for everyone.
In other words, our bank wasn’t merely trying to shift products online to cut costs or offer some convenience. Our products aimed to work, behaviorally, within the daily lives of Kenyans as reliable tools.
Now, perhaps, you can understand my audaciousness. Owing mostly to the bank’s executive team preceding me, we’d developed an economically sustainable and mutually beneficial way to bank the poor.
But Why Would Amazon Care About This?
Now the obvious question is why anyone would think America is a good place for such an ecosystem. After all, America is fabulously wealthy, right? Moreover, why would a company like Amazon — an online retailer — be interested?
Well, it turns out, over 60 million American adults were either unbanked or ‘underbanked’ in 2017. This means they were either unable to make full use of financial services or were paying far to much for the ones they were using.
And while most Americans in this contingent are still economically better off than most Kenyans in this segment, the unbanked in America struggle.
For example, if we fast-forward to the present, COVID showed that being unbanked or underbanked creates substantial, basic problems. Unable to use non-physical payments due to social isolation measures, for example, many of the unbanked were unable to access basic food and product delivery services, since they lacked accounts.
Obviously, I didn’t foresee any such scenario in 2017, but I did see Amazon’s unique positioning as a provider of access. This positioning only strengthened during COVID. Amazon, then and now, can enable customers — banked, unbanked and underbanked — to manage the ups and downs of economic life, if it wants to.
The key challenge is establishing the same sort of win-win situation. Amazon customers needed to have problems we could solve with the giant’s product and seller ecosystem.
As an aside, it’s worth explaining why I didn’t approach banks with this platform.
Creating debtors at high interest rates is typically the only way banks know to do business. Even though bank CEOs have claimed to target the unbanked for years, their efforts have done little to reduce the unbanked number. Indeed, COVID might have even led to the number of unbanked ballooning as defaults increased.
Moreover, it’s a full, a full 3 years plus since I approached Amazon and banks are still scrambling to undertake the digital transformations they always claimed were so important back then. Hence, my bet on approaching Amazon versus a mega-bank was a good one.
Or was it?
Bezos’s Response
The next day, I received a response email. I’d love to tell you it was from Jeff Bezos himself, saying something like,
“You’ve got some balls man, but I like it! Why don’t we set a time to talk?”
But it didn’t happen that way.
One of his army of assistants sent me a polite email explaining that she was answering on Jeff’s behalf. She said she’d personally forwarded my mini-proposal to Amazon’s Business Development Department. Specifically she said,
“Jeff has empowered talented people on this team to work closely with and make strategic decisions about these issues. I feel confident entrusting your inquiry to them. If your proposal would contribute significantly and directly to our business goals, you will be contacted.…”
I was never contacted. It was clearly a boiler plate response adjusted to offer a bit of personal feeling. However, I shrugged it off until…
Amazon moves into banking the unbanked??
That’s right! Some time later, I see an announcement that Amazon has started a program with Synchrony Financial to ‘bank the unbanked’. Although using credit cards and not more sophisticated payments methods, the objective of the collaboration has similar scope to my pitch.
The Amazon collaboration is called: “Amazon Credit Builder,” as reviewed here in this Medium article. The product line’s aims are to aid people in developing credit histories solid enough to later borrow on better and larger terms.
Now, I’m not suggesting Amazon, Bezos or his secretary took my idea. I’m suggesting they weren’t ready for it at the time. And that is perhaps the principle lesson I learned, “cold-pitching” a gigantic company an innovative idea:
Big companies aren’t interested in innovation for innovation’s sake, even if it makes sense economically. They’re looking at the bigger, strategic picture for their outfit.
Undoubtedly, Credit Builder will be profitable for Amazon and Synchrony. It’s very traditional and straightforward. It probably meshes well with Amazon’s existing product lines, its customer base and its internal strategies.
At the same time, it sounds incredibly boring and it’s not what I’d expect from a company known for innovation, in a general sense. Indeed, as I explained above, traditional credit cards are not innovative (or cool) or particularly helpful at solving problems for the unbanked.
It feels like we’re observing a bunting instead of a potential home run or essentially the slowing down of a once fast-moving, startup.
For one thing, building credit histories is important, yes, but for creditors — not borrowers. Borrowers want products and services, so making them jump hoops isn’t something they prefer to do. Moreover, credit cards have been around a long time and still haven’t solved the unbanked’s or underbanked’s problems.
Indeed, one expert in blockchain and other technologies, an area many aiming at the unbanked are exploring, points this out in detail. He even argues companies should stop using the phrase, ‘bank the unbanked,’ when their products don’t address the core reasons for unbanked and underbanked status in the first place.
Thus, it’s reassuring to see that my presumptions about Amazon’s strategic goals were not far off. However, it’s disappointing to see Amazon’s and Synchrony’s less than inspiring stab at achieving them .
Nonetheless, the whole experience offers many useful takeaways — both for me and other innovators…
The Takeaways
- Bezos probably never got my email, but even if he had, I should have crafted it differently. As I said, I was audacious and perhaps even a bit arrogant in my tone. I’d let my enthusiasm for what my team accomplished and what I hoped to bring to the table get the best of me. That’s a sore lesson to learn, especially for many of us, working in the arena of innovative tech. It’s easy to see the many possibilities without considering the practical constraints of those we’re pitching . These constraints include their never being able to take the exact same view of things we can. It would have been better had I sent a very short email, detailed only enough to get a meeting. Had I gotten that meeting — and more information about what they were doing — I could have offered a spectacular demonstration of what I was seeing.
- When companies become big, they pretty much all become alike, no matter how innovative they once were. At the same time, I believe I imagined an Amazon that probably no longer exists. It’s still a brilliant company, but it’s leading role as an innovator is probably past it. I made the assumption that the same innovative culture that pioneered APIs and cloud services, continued perpetually in its approach to customers. But then came Credit Builder. And while a conservative move like Credit Builder might seem particular to Amazon, it’s actually in line with the data. Over the last 4 decades, and spanning 30 countries, something called “Bowman’s Paradox” even predicts it. The Paradox is that companies which do well at an early stage tend to become overly conservative thereafter. By similar token, companies that start doing poorly, tend to crazy bets to get themselves out of the performance hole. The moral of the story for innovators is that successful companies seem to prize innovation until they no longer believe they need to.
- From a performance and investor’s point of view, this isn’t a good thing. Bowman’s Paradox suggests things may not bode well for Amazon’s investors down the road. Yes, the pandemic led to astronomical profits for the business, but that was an unanticipated, Black Swan. How Amazon builds its business for years to come will tell whether it falls prey to the Paradox. In the meantime, the whole suggests another paradox, all on its own. It appears, even though Big Tech companies have the greatest customer reach known to mankind, their size may prevent them acting on that reach in ways that benefit customers or even investors.
Concluding Thoughts
In any case, nothing said here should be taken as trashing Jeff Bezos, Amazon or Synchrony. Rather, the point of my story is that, while innovators should be fearless, they should be prepared for such paradoxes. The world of big companies and partners may not be ready for their innovations, even if markets are. That offers an additional caution for founders of innovative businesses. By nature, these people see markets for their innovations. What they may not see — and what might hurt them, however — is the long road, often paved by giants, that doesn’t necessarily go in the same direction.
