Growing Your Product – Data Points

Product Growth - Data Points

A network of data points can help you spread the net to better understand you products performance and learn about your customer. You will no doubt at this point have a range of growth hypotheses which are tactical and strategic; each of which having different time lines for analysis.

To help understand what data you need to collect, I’ve shared below 5 primary categories that should help. These are groupings which I have used to help trigger useful questions to improve product value.

  1. Market 
  2. Customers
  3. Finance
  4. Operations
  5. Growth Hypotheses (Often Overlooked)

Having a spread of KPI’s and Data Point is important to better understand how your business is navigating against your growth ambitions. By triangulating a range of KPI’s which span across different areas, you are better positioned to see cause and effect and will find yourself better informed to make strategic and tactical changes. Although this may seem intimidating, many of the data points shown here can be populated or retrieved automatically if you have CPM tools or operational systems in place such SalesForce, Zendesk, Jira Service Desk, Hubble and more.

The range of categories can be extended or altered as you see fit in order to meet your business needs and domain. For instance, Pearson have a whole branch of categories on Learner and Efficacy Outcomes for all their educational based software. This supports the global strategy that all products must demonstrate efficacious benefits.

A key point to consider with all the metrics and data points above is to be clear on the timeline considerations. Each of the metrics will need to consider seasonality and market patterns. For example, a high majority of fragrance sales spike in the months approaching the Christmas period. Also when measuring more complex lagging indicators such as efficacy or lifetime value of the customer (LTV), this might take more than a quarter.

You will need to decide when a data points will be best measured in reference to time in order to meaningful. Constant micro-measurements might be constructive in some areas, but may invoke negative knee-jerk reactions in others. You may also discover that there are leading indicators which could be added to the above, which allow you to react before the review. An example of this is where some companies are able to measure social media engagement as an indicator of future sales with a percentage of confidence.

Sample Data Points

Expanding on the 2 of the 5 categories above, I’ve attempted to provide an example of typical data points you many consider within Market and Customer. These are data points can be expanded on or altered to suite your business model, domain and product type.

Market Data Points

 

Data Point Explanation Learning Benefit
Market Threat & Opportunities What new changes are happening that could impact your strategy or tactics. Consider if you were a local driving firm in Amsterdam and you suddenly heard about Uber for the first time. Is this a potential threat for the future, or also an early indicator of an opportunity for your local market. Could provide insight whether a new direction is needed or not.
Total Market Size Whether a new or existing market by customer segment or geography, you’ll want to know the potential to position the investment into your product or business. Consider the Total Available Market (TAM), Serviceable Available Market (SAM). Consider the Total size of paid music consumption as the TAM and the percentage of which Streaming takes as SAM. Knowing the market size by TAM and SAM will help understand the potential revenue and trend to indicate change.
Total Market Share This is considered to be the Share Of Market (SOM) and is the percentage share of SAM. This can be referenced against competitors SOM and will provide useful trend data which can be pretty interesting as new technologies emerge. What percentage of the music streaming service do Spotify and Apple Music have today for instance. Knowing and tracking the SOM against the SAM can help you understand growth against competitors and new technologies.
Competitors It’s useful to track your closest competitors and see how they are progressing in the market. This will give you insights of progress as well as threats and opportunities. Be careful not to be too loose your way by becoming reactive with a “Me Too” strategy which could consume your efforts, diminish innovation potential and could kill your business. Knowing your competitors and market gives you a better triangulation of your overall market position and trend.

These data points are very useful when measuring relative performance. Where many companies provide hard metrics and reward incentives for achieving targets in the absence of competitive trends, they may in fact be rewarding or incentivising poor performance or conversely not recognising good performance.

Consider that you set a growth target of 10% for a given time period. When you review the performance at the given check point and find you have achieved 12% you might consider that excellent. However let’s just say you know know your 3 closest competitors each grew 20%, now is that 12% o attractive. Conversely let’s say you grew just 8%, 2% short of your target. Now with the Market data you have, you have learnt that your 3 closest competitors grew on average 2% each. That additional information reveals that you are growing x4 times faster than your closest competitor.  

Customer Data Points

Using Dave McClure’s Pirate Metrics as a category grouping, I’ve broadly arranged some points that could considered. This doesn’t aim to replace or offer a different version of the Pirate Metrics, but is simply a reference to sensible growth and funnel categories.

Category Data Points Explained Learning Benefit
Acquisition Channels How do you find customers. What channels are you acquiring customer from and which ones are most effectives. Consider partner networks, Ad Words, Referral campaigns, Promotions and so on. Knowing this allows you limit wasted investment in some channels to free up capital to double down on others.
Campaigns If you are running specific campaigns across a range of channels, be sure to isolate the events. Related to the above, this will help discover and maintain an effect engine of growth.
Partners Partner networks and joint ventures may be essential for your business to grow or could hinder your business. Consider how some of the world’s fastest growing companies expand, many rely on regional partners, particularly in enterprise environments. Will help you learn what qualities are needed in new partners and will help you access local markets.
Customer Cohorts Breaking your customers into specific cohorts will allow you to scientifically learn how effective you acquisition process and product is working. Learn which is the most effect growth engine.
Activation Customer Cohorts You need to know which customers cohorts you’re acquiring and which activate. You’re looking to learn who to attract and when you get them how to turn them into customers. This might change or alter as you grow from early adopters through to the early majority and so on. You might be attracting the right or wrong customers and/or have ineffective funnel that need refinement.
Time To Value When you have acquired a potential customer, how long does it take for them to become a paying customer. Some customers might ponder sign up for some time, how do you keep them engaged. It’s not all as simple as signing up to Facebook instantly. The cycle time is key to learn how to optimise the funnel.
Retention Age & Stage What percentage of customers drop off and when in the relationship with your product. If you lose 20% of your customers on a monthly basis, why and what can be done. As the product changes with the environmental factors around you, this is a signal worth observing. Helps you pro-actively engage with customers to extend their custom and learn what more value they need. Health indicator for competitive and environmental landscape.
Referral Number Referral could be the most powerful growth strategy. Consider the now infamous and transformational Dropbox example. Will also contribute to total LTV of the customer. If a single customer spends $100 in their lifetime. Insights into your growth engine and LTV.
Channel Which channels and platforms do your customers use to refer friends or colleagues ? Consider Gousto the home cooking service in the UK who have referral as part of their growth engine. Knowing which channels their customers use most helps complete the loops for the referral to be most effective. Provides insights which channels to invest in and support to optimise.
Activation Secondary link back into the Activation and Acquisition paths specified above. Helps provide more depth to your growth engine and better understand your customer funnel. Adds to the knowledge of your growth engine and LTV which provides insights to projected revenue
Revenue LTV Knowing the average Lifetime Value of the Customer is key to understanding your business model. How much is each customer worth over a given time. Should be continuously reviewed as it could change as you expand your product. Key to understand, revenue and profit.
Average Transaction Value Your product might experiment and change price points overtime with improvements or competition. This can affect the total spend.

Consider a SAAS model. If you increase the monthly cost is it more or less valuable when examining LTV ?

Understanding your price point for market adoption combined with LTV and acquisition costs gives you a more complete picture of revenue and profits.
Engagement Time On Task When the customer uses your product, how long to they spend on each of the specified tasks.

If I’m looking for customer to engage with content such as media, maybe time of task is a good indicator. The longer people on average customers spend watching our latest video could be good. On the contrary if there is a customer job to be done, maybe a quicker time on tasks would delight the customer. Consider a lengthy sign up form. Longer times on task could yield higher drop off and cost.

This can be a positive or negative indicator on the effectiveness of your product satisfying the customer job to be done. This needs to be contextualised on a feature by feature basis.
Frequency How often does a customer engage or re-engage with your product or service. This is a key factor for sticky growth engines. You only have to look at how Facebook continuously and artfully invoke integration with alerts and messages to see how members are drawn back into the platform. Many apps which rely on a freemium based model and in game upsets actively monitor this. The frequency engine then triggers free credits or messages to re-engage the customer. A healthy indicator and potential leading indicator for the likelihood of renewal and customer LTV. Provides you with opportunities to know when to action engagement or how to improve the product.
Task Completion Related somewhat to Time On Task, task completion can sometimes be more effective metric of engagement. Related to the customer job to be done, the task given to customers is what they usually pay for. Monitoring the rate of task completion can indicate product quality and effectiveness. The latter is key for customer retention.
Satisfaction NPS NPS has become an effective indicator of customer satisfaction. You can use NPS at a transactional level to review an event, such as post delivery of a service. You can also review NPS at a relational level which should reference your competitive space. An indicator to see how you are doing overall in the eyes of your customer. A key KPI for overall performance and potentially a very powerful leading indicator to use.
CSAT As with NPS, Customer Satisfaction Scores can provide relative overall performance overview. Is yours increasing or decreasing and to what cost. Similar to NPS benefits above.
Refunds & Support Cases If you have a customer support function, you also have a font of knowledge directly from your customers on what to improve. Metrics to consider include volume of calls/issues, refund cost against a clear categorisation of type and severity. Insights and direct evidence on where you can improve services and products to better serve the customers. Directly impacts revenue and growth potential.

The data points and categories above are more effective when cross-referenced as a complete picture for review. Having a view to each individually although may provide key insights, could be more effective when looking at the correlation across the spread. These will not only help to explain performance, but will also help predict future trends.

These data points allow you to have a meaningful conversation about the customer behaviours and potential future revenue streams for the future as well as a much more informed view of the product roadmap. For instance if you have a spike in specific in support cases, shouldn’t your roadmap look to directly address some of these revenues. Alternatively what about if you can display information on retention or customer LTV and regular reviews see this increasing or decreasing? You should know why so you can capture learnings to capitalise on and better serve the customer.

Data & Learning Organisation

Now this may seem like a lot of data! However these data points will go a long way to helping you understand which direction your business is going and what decisions to make next. You are free to extend the data points to make them more useful for your business.

What needs to be explicit across all these data points is that they spread across the entire organisation. Supported by a culture of curiosity this can help you become a learning organisation. What we mean by this is that in most enterprises, data is solid by function and rarely seen across all departments. For this to take effect, you need to ensure your organisation has clear goals that bind the functions to contribute to these goals. This isn’t a hunt for blame, it’s about every function working together and contributing on the journey of growth and success. This means you might not see the big picture unless you can collectively see how the spread of data correlates.

A key point to raise here is that the data over time will reveal a trend. This data alone won’t have all the answers, but will surface questions. Questions which will allow you to build, measure and learn and grow your business.

If you find this post useful or have any questions or feedback, please comment below. If you use and refer to any of the details in this post, I would appreciate a link back or reference. You can follow me on @craigstrong 

If you’re interested in this topic and more, you might be interested to know that we are exploring this topic in a soon to be published book covering Lean Enterprise Product Development through the lens of a Lean Enterprise Product Lifecycle. This book is being written by myself in collaboration with Sonja Kresojevic and Tendayi Viki. Details will be announced over the coming months.

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