Acquisition project | Avaz Inc.

About Avaz

Official website- Avaz Inc.

Avaz is an India-based, app-first company building Augmentative and Alternative Communication (AAC) solutions for individuals with speech and communication disabilities.

Users tap pictures/words to build messages, and Avaz speaks them out in a clear voice—enabling communication of needs, wants, thoughts, and emotions.

Avaz is used by individuals with autism, cerebral palsy, aphasia, apraxia, and cognitive impairments, and is designed to support both everyday communication and broader development such as language acquisition and literacy.

Founded and built in India, Avaz has played a pioneering role in introducing and mainstreaming AAC adoption across Indian homes, therapy centres, and schools over the last decade. Today, “Avaz” is often used synonymously with AAC within Indian disability communities, reflecting strong brand trust and early market leadership.

Avaz operates as a subscription-based software product, available on Android and iOS, with usage spanning parents, therapists, educators, and schools. While the product is distributed digitally at scale, successful adoption depends heavily on caregiver implementation, contextual guidance, and sustained engagement—making Avaz both a product and a behavior-driven intervention system.

The product is built with inputs from SLPs, and assistive-technology experts, and emphasizes usability and caregiver/partner adoption through capabilities like easy customization and structured vocab approaches.

Disclaimer: All analysis, observations, metrics, and insights in this document are strictly limited to users with the country code India.

Entire concept is viewed from the Product Perspective.

Why Acquisition Is Framed from a Product Perspective (At This Stage)

In a mature product, acquisition is rightly owned by marketing — driven by ICP segmentation, messaging, channels, and CAC efficiency.

However, Avaz is currently in the PMF Discovery stage, where the primary risk is not inefficient marketing, but unclear product signal.

At this stage:

• We do not yet know what activation reliably looks like
• We do not yet know who succeeds without heavy manual intervention
• We do not yet know which early behaviors predict retention

Therefore, acquisition is framed from a product learning perspective first, not to replace marketing, but to enable it.

Marketing-led acquisition before activation clarity amplifies noise, not learning.

Once activation is predictable and repeatable, ownership naturally shifts to marketing prespective.

This document intentionally precedes that handoff.

In Acquisition stage, every product will be in any of these stages and the acquisition goal and process changes in each of these stages:

                         **IN WHICH STAGE IS MY PRODUCT?**

“Before we grow, we must see clearly.”

As of November 2025, Mixpanel shows ~2 lakh unique IDs, but that number alone doesn’t define reality. In the sense, it doesn’t mean we’re a mature product or a scaled business. In fact, we still don’t know which lifecycle stage we’re actually in — PMF, early scaling, matured scaling or nowhere close. Real time examples -

1. 1. Instagram Threads.

What happened:

• Threads launched and hit 10 crore signups in 7 days.
• Headlines called it “the fastest-growing app in history”.
• But retention collapsed by week 3.
• Daily active users dropped
• Meta openly admitted they didn’t have PMF yet.

Lesson:

Huge signups didn’t mean maturity. PMF was still shaky. More users ≠ product fit.

1. 2. Airbnb (early days)

What happened:

• Airbnb got thousands of “listings” early on.
• But almost no one actually booked.
• Founders later said:
  “Our numbers looked big, but real usage was tiny. We didn’t have PMF at all.”

Lesson:

Top-line numbers looked mature, but core loop was broken until fixed manually.

That’s why we need to cut through assumptions and understand the true lifecycle stage of our Avaz AAC app. Without this clarity, anything we do — ICP selection, acquisition, activation, retention — becomes guesswork, not strategy.

Our goal isn’t to make the product look good. Our goal is to see where it truly stands, based on evidence, not hope.

👣👣 Where are we now?!

For the purpose of acquisition and growth strategy, products broadly move through three stages.

STAGE 1 — PMF (Clear ICP, is the product solving the problem, is activation predictable, is retention flattened)

STAGE 2 — EARLY SCALING (PMF Achieved for One ICP)

STAGE 3 — MATURE SCALING.

To understand our product’s stage, we should have clear answer for these questions:

1. HOW activation happens (Activation system)
2. WHO gets activated (ICP system)
3. WHETHER activation predicts long-term retention (Retention system)

• Activation System
  Ask: HOW activation happens?
  Honestly, there is no single behavior, no single event, and no single moment that reliably marks, “This is when a new user becomes active.”

  In short, Activation is currently not standardized across users.

• Retention System
  Ask: WHETHER activation predicts long-term retention?
  Retention can be measured only on users who reached activation. since activation is undefined, all user retention looks like noise.
  
  However, Retention was done on all users as follows:
  https://mixpanel.com/s/135amc
  Glimpse of what the curve shows:

  This weekly retention confirms Avaz AAC app do NOT have PMF for in the Indian Market.

  BUT…
  There is a solid chance that a few sub-segments DO show early flattening and decent retention.
• • After onboarding, 67% disappear within 7 days.
  • Immediately, lost 75% of users by Week 2.
  • MID-STAGE DECLINE (Week 3 → Week 8) - Steady decline every single week, no breathing space, no stability.
  • Curve flattens around 9–10% in (Week 10 → Week 20). However, this is not stabilization. It’s statistical noise caused by: a mix of different parent types, SLPs, School devices and Incidental opens.
• ICP System
  Ask: Do we know exactly which parent type (ICP) succeeds?
  Avaz AAC app was built for “Anyone who has developmental/communication disorders” - which is NOT an ICP.

  ICP definition is the root of MANY of our current problems — retention issues, activation issues, low predictability, no PMF clarity.

  Avaz AAC app DO NOT have PMF across all parents.”

  BUT…
  We have PMF pockets inside our user base for some ICPs.

📌1. Activation is currently not standardized across users.

2. Unable to predict long-term retention

3. No clear ICPs defined </aside>

📌Working Product Stage Assessment, Avaz AAC app (in India) is in -

“PMF Discovery stage with strong early PMF pockets”

In this stage, Our immediate focus is to identify early in-product behaviors that reliably predict long-term retention. In other words, we have to define a practical activation hypothesis grounded in observed PMF users, before formally defining ICPs or scaling acquisition.

⛔ **CHANNEL SELECTION FRAMEWORK**

As mentioned before, the acquisition changes with the stage.

We are in a PMF Discovery stage with strong early PMF pockets.

In simple terms:

• Some users clearly get value from the product and keep using it.
• Most users drop off very early.
• We are still learning who the product really works for and why.

At this stage, the job of acquisition right now is not growth. It is learning.

In PMF Search, a good channel is NOT:

• 1. lowest CAC
• 2. highest installs
• 3. fastest scale

A good channel is one that maximizes:

1. 1. Activation likelihood
2. 2. Early retention
3. 3. Feedback richness
4. 4. ICP clarity

We already have these channels:

• Website
• Facebook
• Instagram
• WhatsApp group
• iOS App Store
• Android Play Store
• Schools
• SLPs
• Therapy centres

The goal was not to add new channels, but to understand which existing channels are responsible for PMF pockets.

“Given the channels we already have, how do we figure out where PMF pockets are actually coming from?”

To identify where PMF pockets are originating, we ran a directional awareness poll among ~975 engaged users via WhatsApp User group.

Note: The poll provides directional evidence about awareness sources among engaged users, not full attribution.

📌This strongly suggests:

PMF pockets are more likely emerging from guided, trust-based channels rather than cold discovery.

Channels that introduce Avaz with context and guidance appear more likely to produce early usage and retention, even when activation is not yet clearly defined.

⛔ **PRODUCT READINESS**

Product readiness ≠

• number of users
• number of installs
• revenue
• feature completeness
• stability alone

Product readiness = Are we ready to deliberately push users into the product and expect a predictable outcome?

Predictable outcome = activation → retention → value realization

We are in PMF search stage and that does NOT mean you are “not ready for the market.”

In this stage, readiness means → Ready for WHAT kind of market behavior?

Avaz AAC is READY for:

• 1. Early adopters
• 2. High-motivation users
• 3. Guided onboarding
• 4. Manual support
• 5. Narrow ICP
• 6. Learning-driven acquisition

Avaz AAC is NOT ready for:

• 1. Broad parent market
• 2. Low-intent users
• 3. Mass marketing
• 4. Self-serve success at scale
• 5. Predictable outcomes across segments

Avaz AAC is market-ready for a specific slice, not the whole market.

📌 IDEAL CUSTOMER PROFILE (ICP)

At the PMF discovery stage, ICPs must be defined by value realization capability, not demographic convenience or channel source.

An ICP, in this context, is a user archetype for whom Avaz can reliably and repeatedly deliver its core value with reasonable execution support.

Based on qualitative interviews, behavioral data, and retention analysis, we consolidate the observed PMF pockets into five ICPs. These are not marketing segments, but product–behavior fit segments.

Research Methodology:

This study was conducted using two complementary approaches to capture both intent and real usage behavior.

1. 1. User Interviews (Qualitative)
2. 2. PMF Pocket Behavioral Analysis (Quantitative)
4. User Interviews (Qualitative)- Details as follows -

Now within this ICP (Highly motivated parents), we will see constraint sub-groups:

• 1. Homemaker
• 2. Working professional
• 3. SLP-dependent
• 4. Multi-child household
• 5. caregiver dependent

These are NOT different ICPs. They are different friction profiles.

Pattern observed:

The Aha moment is the gate.

⛔ 💡Activation event SHOULD be something that correlates with the CORE VALUE, not simplicity.

Activation Hypothesis:

For PMF discovery, we now freeze the following activation definition as-

Activation occurs when a child successfully performs the same functional communication (e.g., “open”, “water”) at least three times across three different sessions, resulting in a real-world outcome.

PMF Pocket Behavioral Analysis (Quantitative) - Details as follows -

During analysis, we observed multiple recurring usage patterns that currently show weak or inconsistent retention. These represent potential future markets or adoption modes, but are not treated as ICPs at this stage.

This is observed among loyal pocket of users — the ones who stay beyond Week 12, where retention stabilises at 9–10%. Refer

Out of the ~150 parents in the PMF pocket, a sample of 6 users was randomly chosen for behavioural analysis to understand their usage patterns.

A clean visual that highlights the Parse Created Date for each user (star ⭐) and shows how their usage days are scattered with no consistent pattern.

• Each horizontal row = 1 retained user.
• Dots = days the user used the app (Tapped Word, etc.)
• Stars = Parse Created Date (signup)
• Usage is random, spread across weeks/months, and highly inconsistent.

Following ICPs were identified -

Note- ICPs above are defined by ability to experience core product value (functional communication) — not by demographics, channels, or motivation alone.

📌 **ICP PRIORITISATION**

📌 Strategic focus (PMF Discovery):

• 1. Prioritize ICP 1 – Motivated Core Communicators
• 2. All other ICPs remain secondary or future expansion segments, not primary drivers at this stage. </aside>

⛔ **Direct AAC App Competitors**

Key Insight - Avaz is the only AAC product with real cultural + ecosystem grounding in India.

⛔ **Indirect / Substitute Competitors**

Note - These often win against AAC, even if AAC is theoretically superior

Key insight - AAC loses not on value, but on time-to-first-visible-win and effort clarity.

⛔ **The Biggest Competitor: Status Quo**

Key insight - AAC doesn’t fail because of rejection — it fails because of abandonment before value is experienced.

⛔ Avaz: Wins vs Lose

Where Avaz WINS-

Where Avaz Loses (Today) -

⛔📌 We do not benchmark Avaz against Proloquo/TDSnap/Touchchat on depth

• 📌 We benchmark Avaz against speech therapy + PECS + “giving up”. </aside>

Competitive analysis shows Avaz loses not on capability, but on time-to-value and effort.

AAC requires high parent involvement and delayed outcomes—only some users can cross this activation curve.

ICP 1 (Motivated Core Communicators) are the only segment that consistently overcomes these constraints and experiences Avaz’s real value.

ICP 1 is not the biggest market, but the only segment where Avaz reliably beats alternatives today—making it the right focus for PMF.

Given Avaz’s current stage in India, our goal is not growth or scale, but to make early value realization (activation) predictable.

📌 MARKET SIZING (INDIA)- AUTISM FOCUSED

For this phase of analysis, we restrict the market definition to children with autism who have AAC needs in India. This ensures market sizing remains tightly coupled to Avaz’s current product scope and usage realities. Reference xl sheet.

How SOM Is Derived (Product-Led Reality)

Unlike TAM and SAM, SOM is constrained by activation predictability, not demand.

Based on Avaz’s actual product data (India):

Average installs/month: ~5,000

Installs/year: ~60,000

Users retained beyond Week 12: ~9–10%

Users showing consistent functional communication (PMF pocket / ICP 1): ~3–5%

Therefore:

60,000 × 3–5% = ~1,800–3,000 families per year

📌Strategic Implication

📌Growth is not limited by awareness

📌Growth is limited by activation reliability

📌Every % improvement in activation directly expands SOM

Example:

• Improving activation from 5% → 10%
  → SOM doubles without changing TAM or SAM

Through qualitative interviews, usage analysis, and PMF pocket identification, we now have clarity on three things:

1. What activation looks like in Avaz?
2. What blocks motivated parents from reaching activation?
3. Which channels tend to produce early PMF pockets?

The remaining problem is not discovery, but repeatability.

To reduce noise, let’s freeze ICP as:

Parents who are willing to learn AAC concepts and persist when guided.

Problem Statement

How do we make activation predictable and repeatable for motivated parents in India?

Today, activation occurs, but inconsistently. Some parents reach it quickly, others take months, and many drop off before experiencing value — even when motivation is high.

Our objective in this phase is to convert activation from a lucky outcome into a reliable system.

At this stage, our objective is not growth, scale, or TAM expansion. Our objective is to turn activation from an outcome we observe into a system we can reliably reproduce.

Once activation becomes predictable across a defined motivated-parent cohort, we can safely layer growth mechanisms such as content loops, referrals, partner programs, and market expansion.