Magic Metrics to Accelerate Marketplace Growth By 1000%

There is no hard written rule towards Product Management, our priorities keep changing, our work practices ever-maturing and processes keep improving; hence we have to make it a point to constantly acquire new skills. This blog is about my own secret recipe from my experience of managing a B2B marketplace’s growth right from scratch to the current status of achieving a 10% market share.

Our B2B Marketplace app for Optical Ecosystem

Whats it takes to run a Product like a Marketplace?
Running a successful business out of a marketplace needs a Product Manager with multi-tasking skills. Unlike E-Commerce Stores, Marketplace has dozen variable factors.

The platform, Associated Brands, End customers (B2B or B2C), Inventories, Sales
Distributer, Store Owner, Manager Who runs the product and much more

I have been lucky enough to build & manage a B2B Marketplace for the eyewear segment right from Zero to 2000+ (Still Growing) Nationwide Retailers. We have had a whole bunch of un-organized business segments of Distributers, Retailers & Brands who used our platform to transact on a daily basis. Having seen all stages of usage cycles right from a change in customer behavior to our MRR hitting the top charts, I felt like a dream come true moment in the end. But for that to happen we indeed had the patience and right data to drive the perfect decisions.

Success happened, but not overnight it came with Discipline and Data Centric Approach

How to define the Early Stage of a marketplace?

It’s never about how old your product is in the market, but how good the product is, that defines your stage. The stage is never defined by a timeline from the product launch or number features or the number of users.

Definition of an early stage

Usually when Users of a new ( non-branded) marketplace don’t do anything other than just login to the application or just do online window shopping(since the trust is yet to be built). That’s how you define an early-stage

Usually, the early-stage product has

An early-stage is always about how much the product is market fit, the maturity of the marketing funnel as well as usage and course sales numbers.

1.Very few people
2.Less time with
3. Heavy load of work
4. Sales expectations piling up from brands
5. Always Unclear in marketing strategy, and
6. Developers firefighting bugs.
7. Additionally, the backend process never seems right,
8. Customer complaints keep piling up,
9. The Support team need to work all the time handholding the users

It’s true that Marketplace Managers must have a real long term vision, but what’s more important in an early stage is to get the basics right and build a working product (ignore building an extraordinary experience for the users).

User & Brand Onboarding Process, Bug fixing process, L1 Support, Lead Generation, DATA TRACKING PROCESS

WHY YOU SHOULD SET DATA TRACKING PROCESS FIRST?

Most Product Managers think that the success of the product lies within the product metrics. But on early-stage Product Managers are like mini CEOs doing everything to make sure the product is successful. In that case, just tracking product metrics won't help. One needs to track a combination of data from all walks of the Marketplace in an incremental timeline and set a process for empowering the employees to utilize it. On looking back, data from each source was our only source of truth upon which we rode. Over a period of time, the process was subconsciously in our system which helped us make any rational scientific decisions.
The following are some of the top-level KPI Categories that we made on each progressing stage of the product:

For business its always about sales numbers in the Marketplace. We tried to calculate how Pre-sales, Marketing, Product Quality, and Product Usage attribute to sales

Let’s see what metrics and how:

Product Quality KPI

The web version of our B2B Optical Marketplace

We launched our beta on Jan 24, 2019. We had amazing responses from all retailers on the idea, so we started small with one distribution center and 10–15 retailers, testing how they are reacting to the idea with product in hand.

We had 2 months of development and our idea quickly got into the market

Like any other early-stage product, our development teams were loaded with work from all sides but the power of data-enabled, along with a bit of common sense, we prioritized on what to go first.

App crash, Customer Issue and bug report per module are tracked and taken action. Sales Stopper, Feature Request, Time to resolve bug is attributed to empathy or financial loss

I always believe that if we can empower developers with the knowledge of either financial implications of what they are building or the ability to understand users pain (Empathy), then the system will work effectively automatically.

Firebase Crashlytics helps to track, prioritize and fix stability issues that erode your app quality. Crashlytics saved us troubleshooting time by intelligently grouping crashes and highlighting the circumstances that lead up to them.

Testers did make the product very robust but, we never know what kind of bugs will popup in real-time for example, due to weak internet signal strength or different device models.

Tracking bugs with regards to pages: for example, we had 50+ customers facing issues in our search results L1 page & Listing pages on particular scenarios that were not traced by our real-time analytics tool, on the contrary, we had 10+ crashes on our PD page. So with just 2+ backend developers, we knew what to take fix first.

Operational & Pre Sales KPI

Post the successful beta launch, we made sure the product was bug-free and on Feb 18th, 2019 we launched our fully furnished MVP open to all our Retailers and Brands in a much more simpler way.

Now that we were open to all brands we thought it would be the right time to onboard and track all the digital inventories in a more efficient way.

My personal opinion is that, at a very early stage it is going to be similar to the Chicken or Egg problem. I remember spending a lot of our discussions on whether the retailers come for brands? or does the brand come when the retails are in? but its best to try it in the market and its always about balancing both. Retailers would want variety and brands would want to reach as many retailers as possible.

Operational and pre-sales metrics that were tracked before the market validates the product

Tracking operational metrics helped us understand our own capability, bandwidth, better resource management, and arrive at our future hiring plans. By Feb 26th, 3 big opticals brands sales were accomplished and had them on board consequently, by March 1st we had around 30 retailers ordering at least once. Now that we are Product-Market fit we wanted to scale up in reaching out.

Marketing KPI

Now that the idea is evaluated, the product was stable on market and business had started making some micro commissions out of marketplace sales. We now started-off with our marketing plan right from March 20th.

Our target was b2b Retailers so we dint go for any traditional ( TV, Offline Ads) or Modern ( Facebook, Google, Instagram) channels instead we focussed on lead collection from various distribution centers.

Each Marketing strategy for every new business model is unique and so is it’s own Funnel. We followed the below funnel,

Lead collection > Filtering > introdution> Awareness > Validation > Consideration > Acceptance > Customer > Happy Customer > Influencer
We Found that more than Excel using Hubspot was extremely helpful

To onboard potential customers continuous retargeting, promoting and building trust is required. In our case, since our target was retailers, B2b marketing involved calling the customers on a regular basis. status.

We ignored any digital marketing or offline campaigns until we archive product-market fit.

The split of customer leads based on sources, also gradually we started tracking which method or channel helped us reach the bottom of the funnel in quick turnaround time. Since we were nascent on the market we understood that it will take time to make the customer aware of the product and it was very essential we take the awareness campaigns religiously.
Avg time to get to bottom of the funnel, no of Leads / Geo, no.of Touchpoints to Create Awareness, Pitch / Campaign, Cost of Acquiring Customer, Projected Customer Payback time, Unqualified Leads Based on Source, Cost per Qualified Lead based on source, Time is is taken each Lead Stage

Product Usage Metrics

Tracking Operational metrics made us iterate on our marketing plan each week with 4 different ideas and constant improvisation helped us reach a short goal of acquiring 300 and reaching 900 + retailers across the city. Our next focus was just focused on product experience.

This is where the Product Managers play come into place, so in reality between fixing bugs, adding feature requests and regression, a small development team will have very little time to implement the analytics tracking system. So in my view, incremental product tracking every week will help balance the roadmap.

The first step is finding out the most used platform and how the users are using the application on different platforms.
After understanding the number of people coming into your product, setting up funnels is the best way to start monitoring user drop-offs.
We compared the above metrics with industry benchmarks and finally lead them to the Cohorts
Product Stickiness Cohort was monitored on a daily basis
Simultaneously, as the Product Stickiness grew out from our cohorts the engagement was tracked
Why track it: Identify the areas where users disconnect with your product; these are optimal areas for experimentation.

Sales KPI

By setting up funnels for every single point of interaction at the onboarding stage, you can get a much better picture of what’s working and what isn’t. Consider grouping customers into cohorts to understand behavior based on the parameters that matter to your business to make the maximum impact from all of this hard work!

Sales define everything, on early-stage weather its top line or bottom line, it is sales which finally is going to help you get the investors' nod their head. These are some of the sales metrics we captured and worked very hard on it accordingly.

Conclusion

Last but not least there can be no words or data to attribute the passion and dedication exhibited by our team towards our vision of organizing the eyewear market rather than disruption. I would take my time in thanking the whole team who not only worked hard but also smartly executed following the numbers rather than gut feel or hunch. Words like Passion, Hard work and Dedication would mean nothing if it’s not fueled by smart data, hope you were able to relate to us and take home something which you can implement in your product. Thanks for reading!

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