How do you know if your product will succeed?

My last interview was in my kitchen, right beside the fridge. At my annual pre-Christmas party in 2015. The CEO said "you may be unemployed in six months but we need you to run supply chain and operations." Seven + years later we are the largest camera volume manufacturer in the world. We chased every customer, solved every early problem they had, and fought as one team to live another day to improve. Hunger makes the best sauce. Luck has a lot to do with it.

I'm a big proponent of generating revenue as soon as possible. Because nothing will validate your idea faster than paying customers. So launch fast with an MVP, get customers and iterate based on their feedback. When creating your MVP, you can and will get feedback from many people. But sift through this to get to the bare minimum product for launch. Because the only feedback that is relevant is from people who have actually paid for your product. I have seen multiple founders get lost in creating the perfect product, only to launch much later to muted success.

Firstly, fall in love with the problem, before trying to validate the idea. Engage with the market - speak and survey potential customers. Dig in to the problem area by questioning the reasons for the problem and the impact of the problem on costs and revenue. Then test a solution/idea, by exploring its relevancy and willingness to pay. The first MVP can even be a concept on paper, to test with potential customers your assumptions and to confirm understanding of the problem area.

Some people do a market research where they ask a bunch of questions to figure out if the product is viable or not. The biggest problem with this is that you are asking people to imagine something that doesn't exist. Companies like Airbnb would've never come into existence if they relied on market research. Instead, use a two-step check. 1. What is this product trying to achieve? What does it do for the user? 2. Identify if there are similar products in the market? How many times do we hear entrepreneurs say that their product has no competition? Even though many people think that their idea is unique, there are three other people who have already thought about it.

?? How do you increase your chances of creating a successful product? Your solution needs to match a problem. (Problem -> Solution Fit) Match your product feature ideas against your future clients pain points. For example, "If I created something that does X for you, would you buy it?" Your product needs to have a place in the market. (Product -> Market Fit) Ensure the market is large enough. For example … you may not want to build something with a very small market size. ?? Like to support this

I always think of Brian Balfour regarding PMF. Can you draw a retention curve where at least a decent percentage of users continue using your product indefinitely. Even if it's 5-10%, if they stick with usage and don't decline to zero, that means you have something sticky for a portion of the population. Then the key, whether it's a new feature or a new product, is digging in with that small base of users to figure out what keeps them coming back and use that to influence your product strategy moving forward.

How do you measure product-market fit? Start by measuring customer loyalty with metrics such as retention, repeat purchases, return rates, engagement, and product usage. Marketing metrics, such as customer acquisition costs ("CAC"), demonstrate that you’re solving a real problem, your messaging is on point, and you have an efficient path to new customers. Beware. Too many founders believe they found product-market fit, only to realize customers won’t pay enough to allow scaling your startup. Pay attention to customer lifetime value ("LTV") and unit economics. Customer engagement and retention is only truly meaningful when your customer has to reach for their wallet.

Try the Sean Ellis Test - a single-question survey designed to gauge how many of your customers consider your product as must-have. The question is: “How would you feel if you could no longer use [product]?” The responses are: - Very disappointed - Somewhat disappointed - Not disappointed The goal is to reach a stage where at least 40% of your users would answer “Very disappointed” if they could no longer use your product. This is seen as a strong indicator that your product has achieved product/market fit.

Measuring product-market fit is like checking if your key fits the right lock. Some of the key aspects that one should focus here are Customer Surveys Retention Rates Referrals Usage Pattern Revenues Customer Feedback If most of these aspects are positive and ticking the right boxes, your product is probably fitting the market well. If not, you might need to tweak your product to make it fit better for the market that you are looking for

PRETOTYPE AND TEST LIKE TESLA As innovation facilitator I like to share how Tesla interested buyers for their first car. In 2003, the founders of Tesla had an ambitious idea (an all-electric 2-door sports car). In order to convince potential buyers to order its car, Tesla created a pretotype of what the car would look like. Lotus supplied Tesla with a ‘glider’ Elise - which was filled with models of key components. This was not a prototype, because the vehicle didn’t function. Tesla was able to show buyers a close proxy for the final design. Tesla asked “Will you put down a $5,000 deposit to have it built to order?” From this test Tesla secured several hundred deposits, a non-trivial result to reassure their Investors.

Measuring product success on the market using metrics to analyze product's performance,evalutaing,for example,the number of new customers and the technical aspects of product according with the standard of the industry sector.

Data-driven improvements are the secret sauce for product success. ??? Consider this: Airbnb increased its revenue by 5-10% with a simple tweak to its photo display. By analyzing user behavior and preferences, they discovered that high-quality host photos led to more bookings. Your product's performance metrics are your compass to growth. Listen to your users, gather data, and fine-tune relentlessly. It's a proven path to success. ????

Developing a successful product requires a strategic approach that emphasizes understanding your target market, establishing clear goals, and continuously iterating based on user feedback. Here are ten key steps to achieve this: ? Targeted Market Research ? Competitive Landscape Analysis ? Define Success Criteria ? Iterative Development and Testing ? Prioritize Usability and User Experience ? Establish Performance Metrics ? Plan for Scalability ? Maintain a Feedback Loop ? Embrace Adaptability ? Measure and Analyse By following these steps and fostering a data-driven approach to product development, you can significantly increase your product's market success.

The way you build your tech product directly impacts how effectively you can maintain it and keep your customers satisfied. Efficient development processes and robust architecture are crucial for long-term success. You will save a lot of money to deploy costumers and keep it updated.

This is tough, because you got feedback to improve certain features, and others to change product scope. How do you decide with limited resources and most importantly time and risk. Sometime adding new feature is easier than changing - and you may end up hurting your current functionality in the process. That is the risk, be careful, here - many software companies - end up creating multiple versions to balance the need - with thoughts of merging back in the future, but that is easier said than done.. this can quickly become very hard to maintain. generally, less is more.. quality over quantity.

To gauge the impact of product enhancements on user experience, you have to measure metrics within users by monthly cohorts. Most people miss this. This approach is vital for understanding user behavior, enhancing retention, and making informed decisions, ensuring that your app improvements genuinely benefit your users.

"What is not measured can not be improved" Setting clear, specific goals and identifying key performance indicators (KPIs) aligned with these objectives provide a foundation for growth. Implementing robust data collection systems and real-time monitoring tools ensures continuous tracking of performance metrics. Regular analysis of this data reveals trends and areas needing enhancement. Customer and internal feedback offer valuable qualitative insights. Transparent communication of metrics fosters accountability and informed decision-making. Utilizing analytics and visualization tools streamlines data handling, guiding iterative improvements. Continuous measurement and analysis are vital for a startup's adaptability and success :)

Monitoring the right product metrics is crucial to ensure customer satisfaction, retention, and growth. Here are some for teams to consider: 1) Net Promoter Score (NPS): Likelihood of customers recommending your product. 2) Customer Satisfaction Score (CSAT): Immediate satisfaction after specific interactions. 3) Customer Effort Score (CES): Ease for customers to derive value from your product. 4) Churn Rate: Percentage of customers who stop using your product/feature in a given period.

Yes, but you need to be able to concentrate on what’s important. Many people get carried away with building dashboards and the result is hundreds of dashboards with thousands of metrics, but this doesn't help them be more effective. Your analysts need to be not only "skilled dashboard conveyor", but be smarter with stakeholders and don't make "dashboard for dashboard" (actually we have "dashboard with dashboard" but it is just for ease of navigation ;)

Monitoring product metrics is essential for understanding how your product is performing and achieving its goals. This guide outlines a ten-step approach to effective product metrics monitoring: ? Identify Key Performance Indicators (KPIs) ? Establish Benchmarks and Targets ? Utilize Analytics Tools ? Track the Customer Journey ? Analyse Funnel Conversion Rates ? Measure Retention and Churn ? Monitor Engagement Metrics ? Gather Customer Feedback ? Iterate and Experiment ? Regular Review and Adjustment By following these steps and consistently monitoring relevant metrics, you can gain valuable data-driven insights to optimize your product and drive its success.

My very first startup failed miserably. We raised 400K and built a really "cool" piece of software. But that's all it was, and people don't generally buy cool. Unless of course, the actual purpose of the product is to make people feel cool, which is, in and of itself, a market. In our case, it was neat but not needed. This is almost worse than building a product that isn't needed and is also a terrible product. People tend to give you false positives when you ask if they like your product, which incidentally is not a good customer development question. Our product was cool, so people told us they liked it, but ultimately nobody needed it, and thus nobody used it. Identify the hardcore need and build products that address that.

In my previous edutech startup we did everything that we could to get our product visible to our customers but competition was fierce, super high and we failed. During our UX/UI phase we did so many interview and got super positive feedbacks from earlier adopters. However, we missed the key points “do customer really need it” .. we learnt I lot from our first “startup failed” and we moved quickly to get another chance and keep fighting for our dream.. failures are ok and make you feel strong, it’s learning and agile adoption.

In product development, failure isn't a full stop; it's a comma. When it comes to product automation in IP, R&D and consulting space, learning from those product fumbles is the key. I was building a product called “Rasayan” using a RPA platform. At first, it seemed like a game-changer, promising faster data. But here's the twist – users found it too complex, and data errors crept in. So, it flopped. But instead of crying over spilled bytes, we analyzed the failure. Discovered that simplicity and data accuracy were key. So, we rebranded it with a user-friendly interface and rigorous QC. Bam! It became a hit. In a nutshell, product failures in automation can be stepping stones to success, as long as you're willing to learn and adapt.

With the excitement of starting up a new business, it can be tempting to launch a business without much forward-thinking. It's extremely important to do your research and to have the right tools and resources in place. The common problem for most entrepreneurs is the belief that they can handle all of the start-up's operations by themselves. Having the right people and the tools in place will help pinpoint any issue when things go wrong and come up with the best solution to prevent it happening again. Having great team support, mindset and tools will help the company grow quicker and become stronger

You also need the attitude and temperament to accept failure and not let it get to you. It can be terribly frustrating but keep the longer term goal in mind.

A common pitfall here is when Product Managers (or company leadership for that matter) spend too much time trying to come up with that "next big feature" or "next big idea" to integrate into their product. You don't really need a 'winning idea' if you're able to quickly test out an MVP version of it. A/B/n testing platforms are much smarter today than before, and you can do some really creative targeting there. Some will even help you build those features for testing! So let the data speak for 'what's the next big feature that will help improve metric x'. Be liberal with A/B/n testing!

It's important to ensure that any innovation to the product is being made because of (a) either a clear commercial need that emerges as a trend or (b) a clear advancement in technology that can clearly differentiate your business or provide your customers with a better service. Lately, the boom in GPT based add-ons to existing products is a clear example of businesses jumping on bandwagons, and are not carefully considering the cost of implementing an LLM model and whether there is any discernible benefit to the end user. Whilst GPT is an amazing tool to enhance access to information, there are many other intuitive ways to deliver information to clients which may be more appropriate.

One way to experiment with product innovations is to use the "build-measure-learn" framework, also known as the lean startup approach. This can be used for all types of innovations, whether they're new features, product pivots, or improvements to existing products.

Very few will enter with a market-defining product or service like OpenAI and the world of generative AI. Key question is if the delta is enough. The difference must be intuitive yet measurable. Price is sometimes a good place to start. If nearly free or the low-cost option, will prospective customers see or feel that delta? Cirque du Soleil is the textbook example of Blue Ocean strategies where the delta is so huge, everyone's cloudy on the competition. Sure the show's expensive, but is it a factor? However, things can't go too far. Too much of a reach (higher delta) might mean a smaller audience. Maybe your product will only be appreciated by those who actually have a viable space program or in a few jurisdictions where regulations exist.

Learn by doing. Too often we stay in development stage and don't make the leap to market. Design Thinking is an iterative process therefore always be tweaking, pivoting etc. By staying in this continues mindset you will always learn by doing and change on the go, take it back, develop, having real market knowledge is valuable for further development and growth. Use Business Model Canvasses to be tweaking also your model next to the product and service. Keep learning by start doing.

Don't just focus on the nuts and bolts of your startup idea - also think about the story you're telling. How can you connect with people on an emotional level and create a sense of community around your brand?

Believe in a product and compare it with possible gaps in the fulfilment of potential customers' needs. One framework for this is the so-called job to be done. Aside from frameworks, you also need to be convinced of the product or service. Because there will always be ups and downs. It is important to be able to continue selling the product with passion, even in bad times. Because the first impression that potential investors gain is through your own appearance. Only when you can convince them as a person, they will look at your business case. And weaknesses in the product will be seen as a reason for rejection or potential for further development, depending on your impression.

Silicon Valley has an AI Problem. The rapid evolution of AI technology, coupled with an overwhelming hype cycle, has given rise to a hive-mind mentality that I have seen in many new startup founders. It feels as if nowadays too many founders are focused on creating companies that use AI as the solution rather than using AI to solve problems they have found. It’s a very subtle difference in thinking, but one that I believe has massive implications when conducting business. Tools used to solve a problem should be picked purely in terms of what delivers the maximum amount of value to your customer. This inherent value it provides should be your product's selling point, not the means of how it is being delivered.

The question asked was: "How do you know if your product will succeed?" ? You don't ? You can't KNOW So instead, figure out what you CAN know Then make it a priority to get that information?? 1?? You will get some info from research 2?? You'll get some from experience 3?? You'll get some from talking to people (the RIGHT people) 4?? And you'll get some by watching what people do when they get to use your product A lot of founders stop after the first 2?? A lot of founders do the third, but not effectively?? Being open to responding to what you learn in the fourth tactic will determine your success?? Start by understanding what the market values?? Then give them something that actually provides it??

Let's imagine your product collects or processes user data. In my experience, ensuring your product succeeds isn't just about making it function properly and finding the right customers. It's also about protecting people's private information and being clear about how your product handles and stores their data. When you're creating and testing your product, you must consider how it might impact people's privacy and follow the rules for collecting, using, and storing their data.