Using AI to Grow Products
AI x Growth PM
One of the bits I have picked this year is to analyse how AI is affecting product management role. I wrote a post around it in January doing a task-by-task analysis for the general PM role.
As a part of this exercise, the next logical step is to look at broad areas of product management - Growth, Product Sense, Strategy, and go deeper into it. In this post, let’s look into how Growth PM gets affected by advances in AI.
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Skills of a Growth PM
Growth is a loosely defined function in product management, in that it could mean various things — getting users to the product, managing churn, monetisation, etc.
All of it requires a set of growth skills. To understand how we can use AI to grow products, we can start by listing down these skills and then see how AI impacts/ enhances these skills.
The first skill is getting a product from 0 to 1 — attaining product market fit. This includes defining PMF, measuring PMF, and improving it consistently to get to a strong PMF
The next skill is understanding how to get users on the product using product. For example, referral is a good example of getting users on the product through existing set of users.
Once the user is on the product, they need to experience the value that the product offers quickly and in the right way. We call this step activation. Activated users (users who have experienced value once) tend to stick to the product longer, and hence this becomes a focus area for the team if the metrics down the funnel like retention, and monetisation, aren’t healthy.
Once you get the users activated, you as a Growth PM need to figure out how to get them back to the product again and again. Retaining users, or strong retention is the hallmark of a good product. This is where core product teams working on the product offering also get involved. These core product teams can work with Growth teams to move retention up.
So far, we have only talked about the user. Another stakeholder of product teams is the business. We need to monetise the product to create a sustainable business. It’s a common myth that monetisation happens after retention. In many education products like Unacademy, Reforge, etc, the monetisation happens upfront before access to the course is provided.
Beyond the five skills we have listed above, there are few skills which are horizontal in nature, i.e. they can be applied across. Designing experiments, or A/B testing is an important skill for any growth PM. It helps the team move faster and gain quick wins.
Data is a another super important skill of Growth PMs. Data informs your experiments, help you track the progress, and also helps you predict growth.
The last skill is building a coherent growth strategy and roadmap, which is needed when to move to product leadership roles. A subset of this skill is Growth prediction through mathematical models.
AI’s Role in Growth
Now that we have listed these skills, let’s look at how AI impacts these skills. Collating the impact across skills can tell us the role of AI in growing products. Note that I don’t cover the impact exhaustively in this section, but I plan to do it in a live session next week. The link for the live session is available at the end of this post.
Product-market fit: AI lets you prototype quickly. This means that iteration cycles can be extremely fast. A fast iteration cycle allows you to test multiple ideas and hypothesis quickly. You can also use AI to analyze user feedback and identify pain points faster.
Product-led acquisition: As building products becomes easier with AI, we will see many companies offering sophisticated features for free as an acquisition strategy. We will also see AI-led or assisted content strategies.
Activation: Activation is where AI can play a transformative role. Think about an AI assistant that guides users through onboarding, which adapts experience in real-time based on user behavior and preferences. AI can also identify friction points in real-time to resolve them. All of this can dramatically increase activation rates compared to static onboarding flows.
Retention: Engagement is a leading indicator of retention. AI can be helpful by increasing velocity of features or content to engages users more. This, in turn, will increase retention. AI can also be useful in conducting and summarizing user research around churn.
Monetisation: Monetisation models are many, and what works for a business doesn’t work for another. Sometimes, an innovation in monetisation model can disrupt an entire industry like subscription did with SaaS. While AI can’t take monetisation decisions with conviction, it can be useful in brainstorming novel pricing models. It can also help you quickly gain understanding of similar industries and help you cross-transfer learnings.
Experimentation: AI excels at hypothesis generation by analysing user behaviour or user research documents. It can also help prioritize which experiments to run. While Growth PMs need to make the final decisions, those who leverage AI for experiment design may be quick in testing more ideas with higher success rate.
Data: Natural language to query translation is available now as a technology. Growth PMs can now ask sophisticated questions about retention cohorts or conversion funnels in plain English and receive instant visualizations and insights. This faster data exploration and analysis means more informed decisions.
Growth roadmap and strategy: Domain research in the AI era has changed. AI can synthesise competitive insights, market trends, and user trends. It can help you identify gaps in the market that competitors haven't gone after. AI can also help in sophisticated forecasting. All of this can make you more confident in growth strategy and roadmap.
Live Session: Using AI to Grow Products
In the session, I plan to cover how AI impacts these various skills, and what to do about it. The session assumes that you have broad familiarity with product management and broad familiarity with growth terms. If you didn’t struggle understanding this post, the session will be useful to you.
Here is the registration link for the Maven session
This would be all for this post! Thank you for reading,
Deepak