In Defense of PLG in Logistics
Welcome to the 114th edition of The LogTech Letter. TLL is a weekly look at the impact technology is having on the world of global and domestic logistics. Last week, I looked at why logistics software pricing is often more about what you lose than what you gain. This week, guest contributor Miles Varghese, CEO of CargoLogik, makes a defense for product-led growth in logistics.
As a reminder, this is the place to turn on Fridays for quick reflection on a dynamic, software category, or specific company that’s on my mind. You’ll also find a collection of links to stories, videos and podcasts from me, my colleagues at the Journal of Commerce, and other analysis I find interesting.
For those that don’t know me, I’m Eric Johnson, senior technology editor at the Journal of Commerce and JOC.com. I can be reached at eric.johnson@spglobal.com or on Twitter at @LogTechEric.
Photo credit: Shutterstock.com / azrin_aziri
Note: It’s a good idea to read this post from a couple months back before you dive into this one. Miles Varghese is CEO of CargoLogik, a forwarding software platform. Miles is a staunch believer in the product-led growth (PLG) model, and in this contributed piece, he argues exactly why it does fit in logistics. Take it away, Miles…
Let’s begin by defining product-led growth (PLG) from a formal perspective.
Reforge.com, the leading closed PLG program, teaches thousands of folks a year how to adopt the latest and newest tech, and apply it in an intelligent, tactical way which ultimately leads to advanced levels of control of the organization, its priorities, products, and growth efforts - along with associated revenue.
This means that when we formally talk about PLG, we’re actually talking about more than just a non-sales led motion. You actually can have both a sales loop combined with product-led growth loops to create new clients, drive revenue, and allow organizations to test unrelated hypothesis that “may lead to growth.” This is a game changer.
How is PLG a game changer? I love analogies and history as they generally provide sufficient indicators to predict what’s going to happen in other sectors and industries. This is easy because the one constant in the process of company building is quite simple: humans and human behavior.
What has happened in sales and martech industries - from thousands of new startups that have entered the scene, disrupting legacy incumbents, and unleashing new waves of innovation and entrepreneurship - is happening now in our space. It’s still early days. One quick indicator of how early it is: you can simply search Google for a martech landscape map and simply compare it to a current logistics and supply chain tech landscape, and it’s a completely different picture. One has already flourished, with many solutions and providers for almost everything you have to deal with on the sales and martech side.
Predictable revenue transformed SaaS forever. Aaron Ross and his elite early sales team created the first framework, process, and analytics for moving sales and revenue-building into a new era of revenue predictability, tied to steps and processes that can be easily taught. Outbound sales quickly shifted from “the art of sales” to a numbers game powered by an army of sales development reps warming up conversations for closers to take new clients and revenue to the finish line.
A company can now can architect their products in such a way to lean on existing natural customer habits to support and validate the PLG model. An example at Cargologik of one of these tactical methods we’re building towards: how often commercial teams for logistics service providers are logging into multiple websites to track cargo. That action interrupts their focus and flow, distracts them from meaningful activities, makes them more prone to errors and redundancies. Instead of winning more loyal revenue, these commercial teams are playing catch-up, being reactive, and quite often losing business to their clients’ other loyal logistics partners.
This is a huge issue in the industry that’s ignored - basic operationalization. Taking the redundant and error-prone activities, and streamlining or automating all the time-sensitive details required around moving cargo more effectively.
The ultimate result of that focus is predictable revenue, a whole new breed of innovation around revenue generation and company building that allowed organizations to take a more quantitative versus qualitative approach to sales.
It meant that a founder could start building a sales team and measuring the funnel at each step. And each of those steps were outreach and contact points designed to build familiarity with target accounts and prospects to turn them into loyal clients asking to expand revenue using the product. It would be something like “13 touch points” (best practice tied to touch points grows every year as prospects deal with more noise, ads, etc) that would be a combination of LinkedIn comments, connection, tweet, Twitter follow, comment, and a series of emails customized at scale through modern tools, to drive folks to talk to the sales team.
One approach is to send 1,000 emails - through repetition, CRM data capture, combined with advanced web marketing and analytics - to solicit calls/demos. Sometimes you might need to send three or four repetitive emails to cut through the noise, and optimize copy with mail servers to maximize deliverability and minimize the odds of being “marked as spam “ when you send someone a cold email (a cold email being when you, or your sales and/or sales development reps, repeatedly email target prospects that fit your solution’s target market).
From those 1,000 emails, your sales and marketing stack would track behavior, responses (CRM), and from there sales teams would attempt to schedule and book calls off positive responses. You’re able to see that a certain percentage of folks responded positively, and from those positive responses you similarly measure how many booked demos. And out of those demos, you see who registered, signed up, and eventually generated revenue.
And after you run through these motions a number of times, patterns will emerge, and you can use those success rates at each step to gauge how many more emails to send, team members to add, demos to target, etc. to back into pre-aligned and conceived revenue numbers and targets. The more data that enters this process, the more it can be refined, the more folks you can hire to drive revenue/sales, but also folks who can be devoted entirely to perfecting your sales process.
This was the difference between the “art of sales,” where we were more dependent on the quality of a rep, paying them accordingly (often premiums for “good” sales people), and hoping that the new sales team adds up (after absorbing the financial and capital risk of building a sales org, which includes VPs, sales reps, realistic commissions, incentives, offices, sales enablement, etc.). It’s a huge burden and risk for a venture to take on, and it also requires an advanced skill set to manage a sales org.
I share this story in depth because PLG represents the next generation of company building. In a PLG model, you focus on client product usage - as opposed to revenue expansion. It bakes a majority (not all in many cases) of the customer acquisition and engagement “into” the product. That means the natural occurring habit loops that the venture is solving for can be improved and augmented - driving more operational value and also commercial value. It requires less reliance on “proper” sales orgs and more reliance on the value being derived from the product. More importantly, it forces a venture (or a venture’s product) to be built around how it can reasonably and predictably influence the set of events that take a prospect and turn them into a champion with minimal intervention.
That means the natural occurring habit loops that the venture is solving for can be improved and augmented - driving more operational value and also commercial value.
PLG reduces dev costs, while driving product usage and venture success. Direct operational value is provided to the client to speed up their “time to value,” which is generally derived from client usage. That client usage, also often being a function of loops, features colleague usage of the product, FOMO, and other elements that are baked into the app intrinsically. Rather than having to engage in long, costly sales cycles, where the venture also has to cover rep costs and their time, PLG enables users to engage organically, from the start, without having to go through unnecessary hurdles.
PLG helps build moats, and and then turns them into oceans. When it comes to providing this value that generates new signups, it is next to impossible (and super time-consuming and costly) for established organizations to quickly and cost effectively adopt. Larger corporations require more activation energy internally to drive change, and in our industry, the shift from legacy/on-premise solutions to the cloud/SaaS is also super difficult to do.
Teams need to be hired. New processes need to be developed. The new processes need to get pushed. And whoever is getting pushed into these new processes needs to adapt from the status quo sale into one more anchored by customer success.
PLG compounds, allowing execs to make better, data-driven decisions faster. The mechanics of analysis, experimentation, and improvement based on sales numbers (and data from those processes) that are hopefully captured in some format will also have to be recreated on the product side. Product-led growth is defined not only by sales, but marketing, ops, and leadership. In short, it touches almost all departments of any organization.
When you are able to effectively instrument your product, add user behavior analysis, and test/measure outcomes, you’re getting closer to a full-fledged PLG program that enables you to design experiments that may be seemingly unrelated and that can be qualitatively and quantitatively thought through, mapped out, and tested against each other.
Things like “should I focus on the onboarding step 2,” or “should I focus on the quotation aspect of Cargologik,” can be modeled quantitatively based on each step of the users flow tied to that feature, function, or utility provider. In a PLG-focused enterprise, there are dedicated teams who can take existing data, leverage tools like Mixpanel and Optimizely, and conduct experiments to validate such hypotheses that may come from business and revenue teams.
And just like predictable revenue, each step of the prospective client’s usage becomes better and more mapped out for optimization. Cohort analyses be run over segments and usage, and then new tweaks and improvements to those users and segments can be executed to improve conversion, positive outcomes. At scale, as you analyze each growth loop and its metrics, you can start building towards products with built-in virality and the revenue that comes with those efforts. You can model and project how each group of users will behave using your product, revenue you can drive, and also areas to focus on for improvement become immediately visible
Small tasks can move the needle in a big way as you continuously learn and optimize client usage and the associated revenue, identifying the drop-off points in usage that might be happening now, or a few weeks from now. You can influence the positive behaviors and build products in-line with customer expectations and value.
Conversely, building everything and “going with your gut” too much can lead to the demise of any startup. PLG represents the framework where an organization can identify areas of improvement that can substantially move the needle on revenue - especially revenue based on usage. It means you can run many experiments, capture and plot results as they relate to the adoption stage of the client and the product’s attractiveness/marketing efforts and hone in on specific tactics, areas, and time frames to enact change in a meaningful way.
This needs to be designed from the get go. To move backwards from a legacy org structure into a “SaaS” company, and possessing those 10x multiples that asset-based companies generally cannot obtain, is next to impossible. PLG requires intrinsic adoption and becomes part of the venture’s culture. Feeding demand, driving revenue, and, in our case, improving the overall shipping/logistics experience between logistics partners and their clients/other partners. It provides for more data, detail, and opportunities, both quantitatively and qualitatively, to grow an enterprise from seed to public corp.
Product-led growth is similar to the advent of predictable revenue, and represents a strategic and tactical way to build your product as well as drive a successful venture well into the future. It provides a culture of nuanced experimentation and testing within venture formation that can apply at whichever stage you fall within the growth curve lifecycle of a startup. It also eases adaptation of your business model within a marketing environment that is ever-changing, competitive, and noisy. It allows both business and operational leaders to align and drive impactful strategy that moves the needle beyond core product usage. Questions with “no great answer” become informed by statistics, analysis, retention and usage, and other data factors that exponentially decrease the normal costs associated with launching a venture.
PLG will be as common as saying “inbound lead” (which in itself was a new concept not long ago) or the predictable revenue of driving sales, revenue, and achieving the escape velocity needed to make it to the next step. Getting to PLG is no easy feat. PLG represents full faith and a bet on the future of buying in SaaS, and thereby company, venture, and product building.
TPMTech Spotlight
I doubt there are many conferences that explore the technology needs and wants of forwarders more comprehensively than TPMTech will. All of which makes this session, on the afternoon of day 2 supremely important. In this session, a powerhouse group of forwarding and forwarding software experts will discuss how technology translates into business efficiency. That means either making the cost-to-serve or cost-to-procure more efficient, or the cost to acquire and retain customers more efficient. Technology has to address one of those two buckets. Really delighted to have my good friend Angela Czajkowski leading this discussion. Don’t miss it. And remember, new registrants can get 25 percent off a TPMTech, TPM23, or bundled pass with the code EJTPM25.
TPMTech DevCon update
Earlier this week, I posted progress on the first ever TPMTech DevCon. Read the whole post here, but I’ll also noted in this newsletter that I’ve refined the topic areas to:
Data standardization
System security
Document and data ownership
Growth models (ie product or sales-led growth)
Scaling from startup to growth stage
I’m looking for discussion leaders on everything but "Document and data ownership" so don’t be shy about nominating yourselves!
Here’s a roundup of recent pieces on JOC.com from my colleagues and myself (note: there is a paywall):
Well, obviously the top news of the week was Flexport letting go of 20 percent of its global workforce. There’s certainly a lot of schadenfreude out there about this, and maybe some justifiable antipathy about the way this was messaged. In either case, most people’s reactions to this news is speculative - does this indicate Flexport is going to be less of a “forwarder” and more of a “tech company” or more of a “supply chain management company.” Or is this indicative of a symptom afflicting a lot of the LogTech emergent companies the past decade (ie over-hiring). Lots of speculation about whether this was an investor-mandated decision or whether this was Dave Clark, Flexport’s soon-to-be solo CEO, making his mark. All of it is speculation at this point. But…I will be having a one-on-one with Dave at TPM23 the morning of Feb. 28. We have a lot to discuss.
The container line Zim is backing a startup focused on cross-border trade finance and payments, a category that is getting pretty crowded. Interestingly, Zim is using some of its pandemic profits not just on a seed stage investment, but in a $100 million credit facility to enable the startup, 40Seas, to finance small importers and exporters. The other tie to Zim is that Zim’s digital forwarding arm, Ship4wd, will integrate the trade finance product into its platform. If you want more LogTech Letter homework, here’s a newsletter from mid-2021 about trade finance.
And here are some recent discussions, reports, and analysis I found interesting:
This market map isn’t perfect, but as I know from experience, no map ever is. Still worth a gander.
Good post here from Schematic Ventures with 2023 predictions from its portfolio companies. Schematic General Partner Julian Counihan will be on a TPMTech panel about what happens next in data sharing with speakers from GSBN and Flexport, and led by my colleague Cathy Morrow Roberson (who has a weekly newsletter you ought to already be subscribed to).
Overdue on a plug for my colleague Ari Ashe’s own unmissable Substack.
Some upcoming events I’ll be involved in:
My guests on the Jan. 20 episode of LogTech Live at 10 am ET will be Charley Dehoney and Liz Ward of ZEBOX America. I’ll actually be doing this one live with Charley and Liz at ZEBOX’s Arlington office. Tune in to hear about acceleration versus incubation and investment, and how corporate partners can help startups make the leap. The best way to keep up with details about my show is to subscribe here.
At 2 pm ET on Jan. 24, I’m moderating what should be a hugely informative and fun discussion with Fishtail.ai CEO Marc Held, CargoLogik CEO Miles Varghese, Tive CEO Krenar Konomi, The Robinson Agency CEO Adam Robinson, and Ruben Huber, director of the OceanX Network on forwarding tech solutions. All five have been past or future TPMTech or LogTech panelists. More details on how to catch this one here.
I’ll be at Manifest in Las Vegas Jan 31-Feb 1, involved in two sessions, including a kickoff session at noon Jan 31 talking about the process journalists use to decide what we should cover. I’m also moderating a session at 11:30 am Feb. 1 with execs from Greenscreens.ai, Convoy, Valoroo, and Innovation Endeavors.
Disclaimer: This newsletter is in no way affiliated with the Journal of Commerce or S&P Global, and any opinions are mine only.