Product Innovation Guide for Product Managers PDF

Product Innovation: A Guide for Product Managers Product innovation is a process of creating new or improving existing products to meet market needs and gain competitive...

Product Innovation: A Guide for Product Managers Product innovation is a process of creating new or improving existing products to meet market needs and gain competitive advantages. It requires deep customer insights, market awareness, and technologies. Power of Product Innovation Product innovation drives business growth. It involves creating new or improved products, services, and processes that provide value and differentiate offerings. Successful innovation requires creativity, research, insights, technology and most of all focus There are many forms of product innovation, each with a unique purpose - new development, improvement, extensions, process, cost, and business model. These approaches help companies stay ahead, meet customer needs, and gain competitive advantage. What is happening in the Market – looking beyond the obvious Gathering insights about their pain points, unmet needs, and desired features. Customer Research  Surveys, interviews, focus groups, and user Market Trends & Data testing. Staying abreast of market trends CSAT -customer feedback allows product Monitoring industry shifts, emerging technologies, and managers to identify opportunities for creating changes in consumer behavior. products that truly resonate with their target analyzing market data and insights, audience. Why and What to build ?? RICE: Reach, Impact, Confidence, Effort Reach 1 This metric quantifies the number of users who will be affected by the feature within a specific timeframe. It's typically estimated using user data and market research. Impact 2 Impact measures the extent to which the feature improves the user experience or achieves the desired outcome. It's often scored on a scale, such as 1-3 or 1-5. Confidence 3  Confidence reflects the level of certainty in the estimates of reach and impact. It helps account for uncertainty and biases, usually scored as a percentage. Effort 4 Effort represents the time and resources required to implement the feature. It's typically measured in person-months or similar units. MoSCoW: Must Have, Should Have, Could Have, Won’t Have Must Have These are essential features that are critical to the product's success and must be included. Should Have These are important features that add significant value but are not critical to the product's core functionality. Could Have These are desirable features that are nice to have but not necessary for the product's core functionality. Won't Have (This Time) These features are not a priority for the current iteration but may be considered for future releases. Value vs. Effort Matrix Value Effort Priority High Low High High High Medium Low Low Low Low High Low the users will be. Kano Model Basic Needs (Must-be) Performance Needs (One dimensional) Excitement Needs Features that users expect by (Attractive) default. Their absence leads to Features where the level of dissatisfaction, but their presence performance correlates directly with Features that users don't expect but doesn't significantly increase user satisfaction. The better these can delight them. They can satisfaction. features are executed, the happier differentiate the product from  competitors. Weighted Scoring In this framework, features are scored based on a set of criteria relevant to the product's goals (e.g., revenue potential, user satisfaction, strategic fit). Each criterion is assigned a weight based on its importance, and each feature is scored against these criteria. The total weighted score helps in prioritizing the features. preencoded.png Opportunity Scoring (Outcome-Based) Opportunity This metric assesses the potential to solve a problem or improve a situation for users. Satisfaction This measures how satisfied users are with the current solutions. Features with high opportunity and low current satisfaction are prioritized higher.  ICE: Impact, Confidence, Ease Similar to RICE but simpler, the ICE framework evaluates features based on impact, confidence, and ease. The formula to calculate the ICE score is: ICE Score = Impact × Confidence × Ease. Concept Development Prototyping 1 Prototyping is the process of creating early versions of a product to test its feasibility  and functionality. Prototypes can be physical or digital and can range from simple sketches to fully functional mockups. This process allows for early validation and helps refine the product concept based on user feedback and testing. Validation 2 Validation involves gathering feedback from potential users and stakeholders to assess the product's viability and refine its design. This feedback can be obtained through user testing, focus groups, and customer surveys. The insights gained from validation can help identify areas for improvement and ensure that the product meets user needs and market expectations. Iteration 3 Product innovation is an iterative process, meaning that it involves continuous refinement based on feedback and evolving requirements. Prototypes and validated concepts are constantly iterated upon, incorporating new insights and improvements. This iterative approach ensures that the product evolves to meet changing needs and market conditions.  Testing and Iteration Testing Type Description Usability Testing Assesses the product's usability and identifies any issues or areas for improvement. This testing involves observing users as they interact with the product and gathering feedback on their experience. A/B Testing Compares different versions of the product to determine which performs better. This testing involves randomly assigning users to different versions and analyzing their behavior and preferences. Beta Testing Allows a limited group of users to test the product before its official launch. This testing provides valuable feedback on the product's functionality, usability, and overall performance. Go-to-Market Strategy Market Positioning Defining how the product will be positioned in the market relative to competitors. This involves understanding the target audience, value proposition, and competitive landscape. Pricing Strategy Developing a pricing model that reflects the product’s value and market conditions. This includes considering factors such as cost of production, target market, and competitive pricing. Marketing and Sales Creating a plan for product launch, including promotional activities and sales channels. This involves defining target markets, marketing channels, and sales strategies. Launch and Post-Launch Activities Rollout Executing the product launch and monitoring its performance. This involves launching the product to the target market, monitoring its adoption rate, and gathering user feedback. Customer Support Providing support to address any issues or concerns from users. This involves establishing a customer support system and ensuring prompt and effective responses to user inquiries. Performance Tracking Measuring key performance indicators (KPIs) to evaluate the product’s success and make data-driven decisions. This involves monitoring metrics such as user engagement, conversion rates, and customer satisfaction. Metrics Metrics are numbers we use as a barometer of how our overall product strategy is going. As a product manager, you're responsible for being the interpreter of this data. Data Informed, Not Data Driven  Data Informed There are factors that can and Data Driven You only use data as one source should go into your decision of information to make decisions. making that are not easily You make decisions solely based Decision Making measured. on data. Data Is Just Raw Information Data Translation User that contribute vs. Users that do not 1 contribute. Data has to be translated into a story that's easy to Product Strategy understand and that clearly indicates what action 2 should be taken. Metrics let you know if your product strategy is working and how a change has affected your product. User Segmentation 3  metrics we select to passively monitor, but also what metrics we choose to actively optimize for. Active Optimization 4 The role of strategy is not only to determine what Priorities -> Metrics Business Goals One way to prioritize what metrics you care about is to directly tie them to your overall business goals and product strategy. Baseline Metric The metric that tells you if you're succeeding. Target Metrics Metrics that when change make the baseline metric change. Example #1: Subscription service Goal In the next 6 months, you need to increase the total number of users that convert from a trial to being a paid customer. Baseline Metric % of new users that convert to paid over a specific time period. Target Metrics % of trial users that log in every day, % of trial users  that access a specific feature. Arget Example 2: Any business ☺ Goal To increase the amount of money each customer gives you. Baseline Metric Individual purchases: ARPU (Average Revenue Per User). Target Metric  LTV (Lifetime Value). Example #3: E Commerce Business Goal 1 To increase cart size. Baseline Metric 2 Average Cart Size. Target Metrics 3 Average Session Duration, % of users that interact with your product suggestions. Metrics – AMAZON, Flipkart, Myntra etc Conversion Metrics they buy. Repurchase / Retention Acquisition Metrics The % of people that purchased. Conversion rate by origin source. % of users that returned (x Based on paid ads. Conversion rate by device type. amount of times / within x amount CPC - cost per click (user clicks your of days). ad). Conversion rate by product / SKU (stock keeping unit). These metrics help you figure out CPM - cost per mille (1,000 users your idea type of user. view your ad). Funnel abandonment metrics - cart abandonment phenomenon: Companies that have more Saturation - how many times they 70% of people that fill out a returning users have more saw the ad before they engaged with shopping cart abandon it before revenue. it. Size Metrics AOV 1 Average Order Volume - how much a user buys on average. You need to track AOV by device type, by source, by returning vs. new user, and by product. Mobile App Acquisition 1 Download attribution - where downloads come from. CPI - Cost Per Install.  Activation Metrics 2 % of downloads that launch the app. % of launches that result in signups. % of signups that result in being a regular user. Retention Metrics 3 DAU: Daily Active Users. MAU: Monthly Active Users. N Day Retention: on any given day, what percentage of your total users launch the app. Clickthrough Rate on your push notifications, email campaigns, or other messaging campaigns. Churn - "dead" or inactive users. App Uninstalls. Mobile App Revenue Metrics Free Apps They make money through ads. CAC (Customer Acquisition Cost). Freemium Apps That make money from in-app purchases or subscription tiers. Subscription: %  of upgrade users, % of upgrades by acquisition source. One-time purchases: % that buy each one, % users that buy multiple types of one-time purchases, # of purchases per month. Paid Apps They make their money from downloads. # of people that pay for downloads. Your main efforts will be focused on optimizing price. Marketplace Revenue Metrics GMV (Gross Merchandise Value) - the total amount that's sold in the market on any given period. Take Rate - the percentage out of the total merchandise value that the platform takes. AOV (Average Order Volume) - it shows how valuable users find the items being sold. User Activity Metrics Liquidity - in the context of a marketplace, it refers to how much of each other's products/services are each of the customer groups buying. Provider Liquidity - the frequency with which a listing creates a sale or transaction for the listing owner. Customer Liquidity - the odds that any given user buys something when they come to a page.  Customer Satisfaction Metrics % orders fulfilled. Average time for fulfillment. Marketplace Metrics Continued Cohort Consistency It tracks whether any change in one side of the market is complemented by a change in the other. Fragmentation High fragmentation (more users are doing less) means that the marketplace is more likely to stay useful. Low fragmentation (a few users doing a lot) could jeopardize the marketplace's competitive advantage, as fewer sellers would have an upward price pressure on goods. PMs need to balance priorities As a PM, you'll be trying to relieve imbalance in your business while simultaneously deciding what needs to be done Strategic Change If you want to make a large strategic change, you can't always rely on data, sometimes you've got to take the chance. Thinking about metrics might take more effort than just doing it and then measuring the results.  Strategic Change If you want to make a large strategic change, you can't always rely on data, sometimes you've got to take the chance. Metrics OKR & measuring the results. Data Vs. Intuition When to choose intuition over data. As a PM, you are trained to analyze and use data at all times. Sometimes, it might be better to use your intuition or gut instinct instead. Data Intuition Optimize user engagement Create something new Readily available and accurate No data available Metrics Vision, experience, intelligence, knowledge When To Use Intuition When you're creating something that's never been done before, there will be no data available to analyze. In some cases, even if you find data on similar products, it might not be that relevant to how your specific product will be received. New Product 1 When you're creating something that's never been done before, there will be no data available to analyze. Similar Products 2 In some cases, even if you find data on similar products, it might not be that  relevant to how your specific product will be received. Tools For Success As a PM, the following are most times vital to make a product successful Vision might be more Industry know how , What not valuable as it drives the team to do ! Experience Intuition Vision 2 3 1 4 Market Intelligence & Data 5 Perseverance