Company / Writing
Field notes.
Research, playbooks and product notes from the team building Markin. One long-form report a quarter, shorter pieces in between.
Growth experiment velocity: Benchmarks and strategies for ARPU expansion
High growth experiment velocity is crucial for ARPU expansion, enabling rapid learning and iterative optimization across large B2C customer bases.
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Optimizing B2C growth team structure for ARPU expansion
Discover how to optimize your B2C growth team structure, leveraging AI to boost ARPU and streamline experimentation.
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How to increase Klaviyo revenue: A Markin guide to ARPU expansion
Discover how Markin layers on Klaviyo to move beyond basic automation, multiply revenue, and expand ARPU from your Klaviyo list with data-driven, customer-specific actions.
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ARPU and churn, measured consistently
What differences between sectors survive once ARPU and churn are defined the same way?
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What guardrail metrics should we track in growth experiments?
Guardrail metrics are essential to prevent growth experiments from damaging critical business areas like ARPU, margin, or customer experience.
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Enterprise tools that use AI agents to grow ARPU
Enterprise platforms like Markin leverage AI agents to optimize customer interactions and accelerate ARPU expansion for B2C companies.
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How to increase ARPU in insurance: strategies for revenue growth
Insurers increase ARPU by strategically optimizing product offerings, pricing, and customer engagement across the policy lifecycle. This involves expanding coverage, precise cross-selling, and dynamic renewal pricing, all underpinned by data-driven insights to maximize revenue per policyholder.
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From campaigns to per-customer decisions
What does a company actually need to move from campaigns to per-customer decisions?
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What happens inside a growth decision
A growth decision is an automated, real-time process that determines the optimal next action for a customer, maximizing their long-term value.
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Lifecycle marketing AI agents: Platforms for 1:1 automation
Several advanced platforms leverage AI agents for personalized lifecycle marketing, differing in their scope of arbitration and personalization capabilities.
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What is agentic growth?
Agentic growth leverages AI to autonomously identify revenue opportunities, deploy actions, and optimize customer journeys for B2C businesses.
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Designing a holdout that can actually detect ARPU lift
How large does a holdout have to be before it can actually detect the ARPU lift you are hoping for?
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How to increase ARPU in ecommerce
Ecommerce brands increase average revenue per user by optimizing basket building, managing replenishment cycles, and leveraging loyalty programs strategically.
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How to increase ARPU in gaming
Elevate player spending and lifetime value in mobile and live-service games through strategic offers, targeted interventions, and data-driven optimization.
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How to increase ARPU in SaaS: action-oriented strategies for growth
SaaS companies increase Average Revenue Per User (ARPU) by systematically optimizing customer value through seat expansion, plan upgrades, annual conversions, and strategic add-on sales, enhancing monetization of existing customer relationships.
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Revenue that carries margin
Which growth decisions raise revenue, and which of them also raise margin?
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How to increase ARPU in streaming
Streaming services can increase ARPU through strategic pricing tiers, bundling, ad-supported options, converting passive users, and re-engaging churners. These methods focus on enhancing subscriber value across their lifecycle.
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Measuring ARPU uplift from marketing experiments
Precisely measuring ARPU uplift from marketing experiments requires rigorous methodology, careful unit of analysis selection, and accounting for various biases to ensure accurate results.
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Customer segmentation vs decisioning: the difference and impact on ARPU
Customer segmentation categorizes users into groups based on shared attributes, while per-customer decisioning applies personalized actions to individuals in real-time. This shift from static segments to dynamic, individual-level interactions is crucial for large B2C companies seeking to maximize ARPU.
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The retention discount line
When does a retention discount keep a customer, and when does it subsidise someone who was staying anyway?
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Offer arbitration: prioritize offers, manage fatigue, and boost ARPU
Effective offer arbitration maximizes ARPU by prioritizing relevant, timely offers while managing customer fatigue across channels. This structured approach optimizes each customer interaction.
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Propensity model features: The best B2C data for predicting customer actions
Effective B2C propensity models leverage a blend of customer behaviors, transactional history, and engagement metrics to predict future actions.
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How to reduce involuntary churn from failed payments
Implementing advanced retry logic, leveraging account updater services, and optimizing dunning communications are critical strategies to effectively reduce involuntary churn and enhance ARPU.
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Your Markin ROI report
Model the revenue a decisioning layer adds on your own base, then get the full breakdown by lever and payback window.
Markin Research
How to run incrementality testing on lifecycle marketing
Measure the true impact of your marketing efforts by isolating causation from correlation through rigorous incrementality testing.
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Churn prediction vs churn prevention: What is the difference?
Churn prediction identifies at-risk customers, while churn prevention actively intervenes to retain them, focusing on actionability and measurable impact.
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The best AI marketing platform for data-driven campaigns
Discover how to evaluate and select the best AI marketing platform for data-driven campaigns, focusing on solutions that deliver measurable ARPU growth through granular, per-customer decisioning.
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The ARPU Report 2026
ARPU benchmarks, spreads and growth rates across B2C sectors, with the decisioning practices behind the top quintile.
Markin Research
The best AI tool to optimize marketing workflows: Markin
Markin, an agentic AI growth platform, is the best AI tool to optimize marketing workflows for large B2C companies, integrating autonomous analysis, decisioning, execution, and measurement to continuously increase ARPU.
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Marketing automation software replacing manual campaign workflows
Marketing automation software replaces manual campaign workflows, enhancing efficiency and ARPU through AI-driven, always-on decisioning and personalized customer interactions.
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An AI marketing tool for personalized email and mobile messaging
An AI marketing tool for personalized email and mobile messaging uses machine learning to analyze customer behavior, predict intent, and automate individualized communications to significantly boost ARPU for B2C companies.
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CDP vs decisioning: understanding the essential differences for arpu growth
A Customer Data Platform (CDP) unifies and centralizes customer data, while a Decisioning Layer orchestrates personalized actions based on that data. Understanding the core differences between CDP vs decisioning is crucial for maximizing ARPU in large B2C companies.
Markin Research
How to reduce churn: a 90-day operating plan
Split payment churn from intent churn, recover the payments first, then treat intent churn by cause with uplift-ranked actions and a permanent holdout.
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Churn prevention vs churn prediction: the difference that matters
Prediction estimates who will leave. Prevention decides what to do and proves it worked. Why an excellent churn model can sit next to a flat retention curve.
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What is churn prevention? Definition, loop and strategies
Churn prevention is detecting risk, choosing the intervention with the highest incremental effect, and proving it worked against a holdout. How the loop runs.
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What is customer lifecycle orchestration?
Customer lifecycle orchestration uses AI to deliver personalized customer experiences by dynamically arbitrating next-best-actions across the entire customer journey.
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Which ARPU expansion strategies actually work for subscription businesses?
Effective ARPU expansion strategies for subscription businesses rely on strategic, data-driven approaches that enhance customer value without triggering churn. These include dynamic pricing, value-based upsells, and strategic cross-sells, all tailored to individual customer needs and rigorously measured for impact.
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Next best action vs recommendation engine: what's the difference?
Understand the core distinctions between these two critical AI decisioning tools for B2C growth and ARPU expansion.
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Define cross-sell eligibility rules to maximize ARPU without cannibalization
Effective cross-sell eligibility rules leverage behavioral and transactional data to present relevant offers, preventing revenue cannibalization and enhancing customer lifetime value. They are crucial for ARPU expansion.
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Win-back campaign timing: how to optimize for ARPU expansion
Growth teams must match win-back campaign timing and offer depth to the specific customer lapse reason to maximize average revenue per user.
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How to Make Save Offer Design Incremental
Design churn save offers that protect revenue without destroying margin by using strict eligibility rules, dynamic offer ladders, and continuous incrementality measurement.
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Churn deflection: the cancellation flow as a decision
Between 30 and 45 percent of accepted save offers go to customers who were staying anyway. How to spend margin only where it changes the outcome.
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How to increase ARPU in telecom
Median postpaid operators grow ARPU 1.9 percent a year, the top quintile 6.7 percent. The five levers behind the gap, and how to measure each one.
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AI agents for marketing: what they are and how to evaluate them
AI agents for marketing explained: the four categories on the market, how to evaluate an agent, and the metrics that judge one.
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Dunning best practices: recovering failed payments before they become churn
Failed payments are 20 to 40 percent of all churn and the cheapest to fix. Retry by decline code and refresh cards before they fail.
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Telecom churn rate benchmarks, 2026
Median monthly churn is 1.1 percent postpaid, 4.4 percent prepaid and 1.6 percent on converged bundles. What separates the top decile from the rest.
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What is a customer decision hub?
What a customer decision hub contains, what it costs to operate, how it differs from a CDP or a campaign tool, and when a decision layer fits better.
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Next best offer vs next best action: what actually differs
Next best offer ranks products and promotions. Next best action ranks every intervention, including silence. The difference shows up in margin.
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ARPU benchmarks by industry 2026: median vs top-quintile
ARPU benchmarks by industry for 2026: median and top-quintile monthly ARPU levels and growth rates across nine B2C categories, with the method.
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Machine learning churn prediction: labels, leakage and the wrong test
Most production churn models fail on label definition, feature leakage, or an evaluation that rewards AUC instead of decisions. The three fixes, in order.
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Voluntary vs involuntary churn: two problems, two fixes
Payment-failure churn is a dunning problem. Intent churn is a decisioning problem. How to split them, who owns each, and how to measure both correctly.
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Einstein Next Best Action: how it works, limits and the decision layer
How Strategy Builder ranks recommendations in Salesforce, where the pattern stops, and how to decide in the warehouse and deliver inside the CRM.
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ARPU vs LTV vs CAC: which number answers which question
ARPU is observed, LTV is forecast, CAC is spend. Using one where another belongs is how a company posts rising LTV while revenue per customer quietly falls.
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Customer winback strategies that pay for themselves
Most win-back programmes mail the whole churned base and count natural returners as wins. How to segment, price the offer and prove causation.
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Next best action software: how to evaluate it in 2026
A buyer's framework for next best action software: decision scope, objective function, causal measurement, constraints and time to first verified result.
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Customer churn prediction: models, features and incrementality
A practical guide to customer churn prediction: which models actually work, which features move the needle, and how to convert prediction into incremental save rate.
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Next best action model: propensity, uplift and ranking
How a next best action model is built: propensity, uplift meta-learners and a ranking function that scores expected incremental margin per action.
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ARPU benchmarks 2026: why B2C spreads keep widening
ARPU benchmarks across eight B2C industries in 2026. The top quintile is pulling away at 2 to 4x the historical rate. What the leaders are doing differently.
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Continuous decisioning: from campaign calendars to always-on 1:1
Continuous decisioning replaces the weekly promo calendar with a loop that ships hundreds of small, causal experiments per week against a preserved holdout. A 90-day migration.
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Opportunity Feed, now with hypothesis provenance
Every candidate action in the Markin Opportunity Feed now carries the signal, segment and prior experiment it descends from. One click to audit or ship.
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Cross-sell without cannibalization: uplift, holdouts and guardrails
How to measure incremental uplift, detect cannibalization and set profit-based guardrails for cross-sell programs that need to defend ARPU, not just campaign response rates.
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What a top data science team looks like in an agentic era
Notes from conversations with heads of growth and analytics at eight enterprises rethinking how their data teams spend the week under agentic AI.
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How to increase ARPU: a framework for B2C enterprises
How to increase ARPU in a large B2C business: the five levers that actually move average revenue per user, and the operating model behind them.
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What is ARPU? Definition, formula and how to calculate it
ARPU calculation explained: the formula, a step-by-step method, variants by business model and benchmark levels from 147 B2C operators.
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Churn prevention economics in streaming and telecom
Where saves compound, where they don't, and why most retention programs in subscription businesses optimize the wrong margin. A CFO-grade view of incremental save rate.
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Agents on the open web: browsing inside a decisioning loop
A taxonomy of agentic browsing, the failure modes we spent the most time on, and empirical results from six enterprise workspaces measured against a preserved holdout.
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Next best action marketing: what it is and how it works in 2026
Next best action marketing explained: how it works, real B2C examples, how it differs from segment campaigns and marketing automation, and what it is worth on a 2M base.
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CMOs on the shift from creative volume to decision volume
Four CMO conversations on what changes when the constraint moves from producing creative assets to routing the right asset to the right customer.
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More writing coming soon