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- 🎯 How June reinvented analytics for B2B
🎯 How June reinvented analytics for B2B
Software that makes you money
Read time: 4 minutes 51 seconds
A product trend I’m obsessed with:
‘Opinionated’ software
Software that guides you towards a ‘best-practice’.
Software that believes in a ‘better way of doing things’.
Software that is designed with a particular philosophy in mind.
This week I got to jam out with Enzo Avigo, founder of June.so - a next-gen analytics tool that I kept hearing about in B2B SaaS circles, because of its unique approach to solving revenue problems for its users.
Enjoy,
P.S. If beautiful product design is your thing, here is today’s treat.
How June reinvented analytics for B2B
Chess Move
The what: A TLDR explanation of the strategy
There’s a fundamental problem with product analytics tools:
None of them were purpose-built for the modern-day B2B SaaS.
Companies like Amplitude focussed on serving the fastest-growing segments at the time they were created - mobile apps, Ecommerce, social networks, and other B2C products.
Through the next-gen B2B SaaS revolution of the past ~5 years, companies developed a totally different set of analytics needs, like:
Activating new accounts
Expanding seat penetration
Preventing seat contraction
Understanding account health
Proactively retaining accounts
Automating / enriching CRM data
Alerting CS teams when to engage
Legacy B2C product analytics weren’t designed for these use-cases, which forced modern B2B startups to hack together their own solutions internally.
In B2B, revenue growth generally comes from improving retention and expansion, rather than from acquiring new customers. The benefit of expansion is that, over time, there is a compounding effect as revenue per customer increases.
The difference in revenue sources for B2B and B2C (source)
June spotted an opportunity: Instead of building yet another product analytics tool centred around user activity, what if they built the first option specifically designed to drive financial results for B2B SaaS?
💡 | Strategy Playbook: Build the analytics operating system for today’s fastest-growing segment → B2B SaaS. |
Breakdown
The how: The strategic playbook boiled down to 3x key takeaways
1. Target the forgotten middle persona
Traditional analytics tools cater to 2 groups of users:
‘Non-technical users’ who need basic metrics
‘Technical users’ who can write complex queries
June noticed that all modern-day B2B SaaS had a new normal persona using analytics tools: People with “soft data skills” who understand complex business metrics but aren’t SQL experts.
12 years ago your typical PM was a SQL-efficient ‘technical’ user’ with an engineering background. Today, most PMs are generalists without a technical skillset, but are comfortable enough with modelling / analysis / AI to research internal data independently.
June started by building specifically for the modern PM:
Simple and intuitive UX
AI-powered plain English querying
Pre-built dashboards, templates, and blocks
PM-native analytics for features, milestones etc.
For many analytics use cases, PMs care more about companies than individual users. Finally, a product with extensive features at this level of aggregation.
“With legacy tools, you’d start with a hypothesis, look into your data, try to find the right visualisation, then have an analyst interpret the output.
With June, you get automatically generated ‘homes’ and ‘one-click reports’ which is essentially what a data analyst would give you in days after interpreting the output - 5-10 graphs with a story, explanation, benchmarks, and recommendations.”
Stole this slide from June’s internal strategy doc. Don’t tell Enzo.
Under the same philosophy, they’ve since added features, audiences, and workflows for the modern Customer Success persona.
The result? Non-technical Product and Success users can understand what their customers do, and take actions to retain them, fully self-serve (i.e. without waiting on data teams).
2. Double down on B2B
June recognised that B2B companies have fundamentally different needs than B2C platforms:
B2C Analytics:
High traffic volumes, optimisation-focused
Demographic user segments (mobile vs desktop, country)
Standard metrics
B2B Analytics:
Complex user hierarchies
Operation-focused insights
Unique metrics (e.g. expansion, contraction)
While competitors tried to serve everyone (and unintentionally ended up focussing on B2C companies which were having their ‘golden age’), June built specifically for B2B SaaS companies:
Account-level analytics
B2B-specific metrics and templates
AI summaries which do the work for you
Individual dashboards for each company
Simple enough UX to be inviting for various user personas
Integrations with CRMs (Salesforce, Hubspot) and communication tools (Slack)
The information you need. Not the information you need to calculate the information you need.
“At the end of the day, for B2B SaaS it's about making accounts successful, not about finding how many times someone clicked a button”
By focusing on this underserved segment, June created a wedge in a market that is now having its own ‘golden age’, thanks to AI.
3. It’s only a valuable insight if it leads to valuable action
After speaking with 100s of B2B SaaS leaders, June consistently heard the same ‘dream outcome’: “I wish this product could tangibly impact our revenue”
Instead of just building dashboards, June created an end-to-end insight system for turning SaaS products into activation and retention machines:
Tells you which customers are likely to churn
Tells you which customers don’t activate
Tells your PMs which features to drop
Tells your CS team when to engage
Automatically surfacing ‘high-risk customers’ = the holy grail dashboard for CS teams
Pegging June’s value to real Return-on-Investment for buyers was a key turning point in June’s adoption trajectory:
“A legacy platform might cost $100k py, which is really hard to justify today since you still need to do the internal analysis to translate the data into action.
June costs $5-20k py, and our customer’s typical Average Customer Value is around the same. This means if you buy June and you activate / retain 1 customer, you breakeven - if you do 2, your ROI is +100%. In practice, the moment you set up a regular motion off the back of June’s workflows, you are consistently generating these wins and June is essentially printing money for you.”
Since recognising this unlock, June doubled-down on ensuring every customer gets a ‘win’ with the tool as soon as possible.
From the moment you’ve added June to your product (<1hr avg as opposed to 1wk for competitor tools), it instantly starts highlighting your best customers (for upsell opportunities) and high risk customers (for retention plays).
“Today’s SaaS are building product with revenue first in mind, rather than a ‘delayed monetisation’ philosophy.
June is for this new generation of SaaS”
Rabbit Hole
The where: 3x high-signal resources to learn more
[3 minute read]
“Why do your first 10 customers get a better experience than your next 1000?”
A refreshingly honest take on the tension between scale and service quality in SaaS.
[12 minute read]
The new-age playbook for building high-trust customer relationships in SaaS:
Why metrics and jargon can distract from what really matters
How to build deep "maps" of customer understanding
Practical tactics for customer-centricity at scale
[4 minute read]
Why can’t B2B companies just copy B2C analytics playbooks?
"Slack has 600,000 customers, but 40% of its revenue comes from less than 1% of its customers"
The same can’t be said for Spotify, Netflix, Calm etc.
Here’s how the downstream implications of this concept have impacted June’s product DNA.
That’s all for today’s breakdown - hope you enjoyed!
Thanks to Enzo + June HQ for putting up with my obsessive questioning.
As consolation, they’re offering Strategy Breakdowns readers an exclusive 25% discount.
Score.
— Tom
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