Developing my own product – Creating a Minimum Viable Product

Now that my efforts to develop the HipHopListings iOS app myself had not provided me with the desired results, I decided to seek help. I got as far as creating a basic app version of my existing HipHopListings (‘HHL’) blog and installing it onto my phone. However, it became pretty clear very quickly that Apple weren’t going to accept my app or that “AppMaker”, the 3rd party tool I was using, were going to submit the app for me. Alex, an experienced end-to-end developer, was happy to help me with developing the app in return for a modest fee. One of the first questions that he asked me however was whether I could provide me him with a short brief of what to build.

At this stage, I had thought about my product vision, assessed the opportunity, created wireframes and even started developing the app myself. What I hadn’t done, however, was define the minimum functionality which needed to be included in the app. I thought I had a reasonably good idea of my target users and their problems that I was looking to solve through the app. Also, I felt I now had a better steer on the criteria Apple use to approve an app into their App Store. I just needed to translate this is into some well-defined features and requirements that Alex could work against.

The challenge was to rein myself in whilst I was outlining the product requirements. I could easily see myself falling in the trap of overdesignining this app, now that I had an experienced developer to help me. I therefore used Tristan Kromer’s version of a mix of the “Lean Product Canvas” (by Ash Amaurya) and the “Business Model Canvas” (by Alex Osterwalder) as a technique to try to keep my requirements as ‘lean’ and ‘minimal’ as possible. This is how I broke it down:

  1. Customer needs and goals (problems) (1) – The key user problems I was looking to address through my HHL app were twofold: (1) how do I find out about upcoming Hip Hop shows in my area? and (2) how do I find out about upcoming Hip Hop releases. Both seemed like fair assumptions to make as I’ve received lot of a feedback on these problems from having done HHL over the past 4 years.  
  2. Customer needs and goals (requirements) (2) – In my brief to Alex the developer I translated the user problems mentioned under 1. in the simplest way possible: (1) enable users to easily view upcoming shows and go to a 3rd party ticketing site (see Fig. 1 below) and (2) enable users to filter listings by area and by date (see Fig. 2 below). I also asked Alex to set up Google Analytics so that I could track users’ actual behaviour and validate some of my assumptions.
  3. Keep it simple – I decided to keep the design of the app as simple as possible at this stage. Let’s get the app approved by Apple first (which can be a real pain in itself), get people to use the app and comment the functionality. Once I’ve established that users actually do find the app of value in terms of finding out about gigs and releases, I can them improve the functionality further and worry more about the user interface / visual design. In his “Lean Product Canvas” Tristan Kromer refers to this approach as ‘trimming the fat’.
  4. Customer needs and problems (3)  Based on previous feedback, I thought it would be good to add a very basic ‘discovery’ element to the app; a very simple ‘Featured’ screen which users can turn to for curated shows and releases which I’d chosen to highlight (see Fig. 3 below). I reckoned this feature would be relatively easy to get feedback on. Firstly, through tools Google Analytics and Flurry I would be able to monitor the number of views of this screen. Secondly, I felt this would be the kind of feature which would be easy to get qualitative user feedback on. I could use both feedback methods to validate one of my assumptions: making it as easy as possible for users to discover new shows and releases will be a powerful proposition for HHL’s (target) users.   
  5. Constraints to consider – One of my personal goals was to learn more about designing for mobile. And learning I did. My original design went largely out of the window as soon as I realised from testing that Facebook’s more traditional split screen view (see Fig. 4 below) would probably be easier to implement and for users to interact with. After all, all I wanted is a clean and simple interface, no frills, and it looked my original designs were probably a bit too elaborate compared to some of the simple user interfaces that are working well (with Facebook, Hailo and Vine as good examples). Also, I realised that I had to update the app’s content manually via a back-end which had to be kept as simple and intuitive as possible. I spent a good chunk of my time think about the user flow involved in uploading, updating and removing the app’s content.

Main learning point: actually putting down my functional and non-functional requirements down was both scary and exciting at the same time. Scary, because I really had to rein myself in and be realistic about technical and financial constraints. Exciting because I could apply some of my ‘lean’ lessons learned to my own app and think about the key value I could provide my (target) users with in the first iteration of my HipHopListings app. If anything, it was great to go from creating my original vision to submitting my app with Apple within a month. As scary and challenging as it felt at times, I felt I had created something tangible that I could launch, validate, learn from and build on!

Fig. 1 – My design for a “Shows” to enable users to easily find out about upcoming shows and go to ticket sites

Fig. 2 – My design for a simple filtering functionality, enabling users to only look at shows in their area or by date

0421'13 Draft Show Filtering V1

Fig. 3 – My design for a simple ‘Featured’ screen which highlights pre-picked shows and releases

0420'13 Draft main app screen (featured)

Fig. 4 – Facebook’s split view mobile app design

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How supermarkets are becoming entertainment platforms

Over the past year or so supermarket giants such as Sainsbury’s and Tesco have started venturing into entertainment content. A good example is supermarket giant Tesco which acquired We7 (digital music) and Blinkbox (video on demand) last year. Its UK competitor Sainsbury bought online entertainment platform Global Media Vault and Anobii (eBooks) around the same time.

I wondered about the business rationale and aspirations that underpin these deals. Do supermarkets want to bolster their physical presence with an equally comprehensive digital offering? Are Tesco and Sainsbury’s looking to take on global content providers such as Amazon, iTunes and Netflix? What’s in it for these supermarkets?

For the purpose of this blog post I’ll focus primarily on video streaming, outlining the key characteristics of this offering and user demands. Let’s start by looking into some of the relevant factors with regard to building a digital video platform:

  1. What does the user want? – From my market research and conversations with consumers, I believe that users are primarily interested in quality content which is easy to access, engaging and – ideally – free. They want to watch TV shows or films across a wide range of devices, with the the experience being as ‘seamless’ as possible. “It just needs to work” is a sentiment that I’ve heard echoed by numerous people, meaning that they don’t have much time for technical glitches, issues when watching content offline or on multiple devices. The average video on-demand customer wants to be in full control of what they watch, when and where. Also the breadth of the catalogue is just as critical a factor; the sooner a service can offer the latest, popular TV shows or movies the better. An interesting development in this respect is Netflix creating its own “House of Cards” series and offering this exclusively to its subscribers. 
  2. What does the business want? (1) – Revenue. User data. Cross-selling. Forgive me for the crude breakdown of these high-level objectives, no doubt the detail behind their business models is probably more refined than that. I’ve tried to break this down a bit more in Fig. 1 below. For a platform like Tesco’s Clubcard TV (powered by Blinkbox) the main revenue source is likely to be advertising. However, just as important is the value the supermarket colossus derives from offering their users an additional, free service and the ability to learn more about their entertainment preferences. Understanding those preferences better will no doubt help in recommending users other content or entertainment related products. I’ve outlined some relevant metrics to determine the customer value in Fig. 2 and 3 below.
  3. What does the business want? (2) – Engaged customers, brand advocates. Perhaps less easy to quantify but not an insignificant factor in this context. It’s much easier to go to another supermarket if they offer the same packet of crisps at a cheaper price. However, if a supermarket offers their loyal customers great free content, you might think twice before switching your ‘allegiance’. There’s still some debate about how successful Netflix’ House of Cards series has been so far in terms of views and subscription increases, but there’s no denying that the programme got people talking and engaged.

Main learning point: previously I had looked at the business models for video on demand providers such as Lovefilm and Netflix. Their subscription based models were relatively easy to work out. With a supermarket chain like Tesco offering free content to its loyal customers, the proposition gets very interesting. It seems like a very effective way to engage with customers, offering them free but compelling content. Similar to the paid versions of on-demand video, I believe that a free content offering will have a bigger chance of success if it provides great content and if it’s easy to access across a range of devices.

Fig. 1 – Breakdown of key players in the video streaming space and their business models

A. Subscription model / Pay-as-you-go

Key players: Netflix, Amazon (Lovefilm/Amazon Instant Video), Apple, Blinkbox and Walmart (Vudu – US)

Key value proposition: Offering quality content and a great – cross-platform – user experience

Business model: Either a monthly subscription fee or pay-as-you-go rental

B. Advertising

Key players: YouTube. BBC iPlayer, Channel 4 VOD, Hulu (US), Tesco Clubcard TV, WatchFreeMovies and Zmovie

Key value proposition: Offering quality content for free and a seamless – cross-platform – user experience

Business model: Free access, no fees required. Use free-access model to attract users to other (premium) content services. Advertising as a main revenue source.

Fig. 2 – Four ways visitors of media sites can generate value (adapted from “Lean Analytics” by Alistair Croll and Ben Yoskovitz, p. 121)

  • Subscriptions – Measure subscription rate to monitor subscription revenue
  • On-site engagement – You can look at a number of engagement metrics (e.g. time since last visit, time per visit, visits per day, pages per visit and time on page)
  • Ad-revenue – Generate revenue through display ads (number of impressions x cost per impression = Cost Per Engagement), affiliate links (affiliate % x sales volume = Affiliate Revenue), sponsorship (e.g. monthly sponsorship rates and number of sponsored banners) and Pay Per Click (Click-through rate x Ad price = Pay Per Click revenue)
  • Sharing –  Generate value through sharing content (e.g. through on-site tools and off-site)

Fig. 3 – Key metrics that media sites are likely to care about (adapted from “Lean Analytics” by Alistair Croll and Ben Yoskovitz, p. 117)

  • Audience and churn  Understanding how many (paid) users you’re adding and losing. For services like Netflix and Blinkbox ‘user loyalty’ is a critical aspect
  • Ad rates or Cost per engagement –  How much money can a service make from impressions based on the content it covers and the people who use the service
  • Ad inventory – The number of impressions that can be monetized
  • Click-through rates – How many of the impressions actually turn into money
  • Content/advertising balance – The balance of ad inventory rates and content that maximizes overall performance


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Book review: “Lean Analytics”

Data are key. Analytics are key. But what does one need to measure? And why?  Experienced entrepreneurs Alistair Croll and Benjamin Yoskovitz wrote “Lean Analytics”, which came out last month. “Lean Analytics” is a great book for anyone who wishes to learn more about validating an idea, building the right product and measuring growth.

In early 2012, I went to a talk by Eric Ries. It was a great talk, with lots of insights that I have since tried to implement on a day-to-day basis. The only thing missing, however, was a steer on how to measure performance in a ‘lean’ context. I felt that Ries’ suggestions around metrics were very much geared to consumer facing products or business models.

One of the questions I had was around measuring the performance non-consumer facing products such as infrastructural or enterprise services. When I got in touch with Eric Ries to follow up on my questions, the short answer was: “wait for a book by Alistair Croll and Benjamin Yoskovitz, due in March ’13.” I kept patient and it was definitely worth the wait.

This is why:

  1. What makes a good metric?  “Lean Analytics” starts off with a basic but very important question: “what makes a good metric?” Croll and Yoskovitz go into four different characteristics of a good metric (see Fig. 1 below) and look at different metric types. For example, I hadn’t yet heard about the difference between ‘leading’ (predictive) and ‘lagging’ (current situation) metrics. This provides an essential starting point for the rest of the book, which delves into which metrics to measure and why. 
  2. Be sensible about data – In Lean Analytics, Croll and Yoskovitz do a good job of putting some caveats around the use of data. Firstly, they stress the importance of combining quantitative and qualitative data, urging readers to “get out of the building.” Secondly, they point out the risks of becoming too data-driven. With the help of Monica Rogati, a well-known data scientist at LinkedIn, they outline 10 common data related pitfalls. For example, businesses should be aware of ‘data vomit’; having extensive data dashboards but loosing focus of those key metrics that really matter to your business.
  3. The One Metric That Matters – Especially if you’re an early-stage startup, Croll and Yoskovitz stress the value of having the “One Metric That Matters” (OMTM). The reasons they provide to underpin this argument are pretty compelling (see Fig. 2 below). When I work with young startups and their often very driven and passionate founders, I tend to to focus their minds on a single metric or value consideration that is likely to really impact their business.
  4. What business are you in?  At first I thought it a bit tedious for Lean Analytics to outline a variety of business models. Surely, most readers should be able to know the difference between an e-commerce model and a media site!? I backtracked very quickly on this thought: not only do Croll and Yoskovitz provide a comprehensive overview of business models to consider, they also offer a great overview of relevant metrics to track per business model. For example, I’m currently working on a free mobile app  and the book offers some useful metrics to consider in this respect (see Fig. 3 below). For each business model the book offers a wealth of concrete suggestions on which metrics to consider and why (using real-life case studies to illustrate).
  5. What stage are you at? The kinds of metrics worthwhile tracking are not only dependent on your business model, they are also likely to vary based on the stage your business is at. Lean Analytics breaks down the different stages that most startups are likely to go through (see Fig. 4 below). I believe the value of using these stages as a reference point is twofold. Firstly, each stage requires its own specific metrics. For instance, as a business you’ll most likely concentrate on different metrics at the empathy stage than when you’re at the revenue stage. Secondly, the book suggests you ask yourself at each stage whether you should move on to the next one, using the relevant metrics to validate your decision making.

Learning point: Lean Analytics is a great fit within the “Lean Startup” movement. The book provides a very comprehensive overview of the different metrics worth tracking and – most importantly – offers a clear rationale as to why certain metrics should be tracked for a specific business model at a given stage. The thing I liked most about Lean Analytics is that all of it makes perfect sense. The book provides a well thought through approach to making sense of something that can be complex and challenging at times: data.

Fig. 1 – What makes a good metric? (Alistair Croll and Ben Yoskovitz – “Lean Analytics”, pp. 9-11)

  • Comparative – Being able to compare a metric to other time periods, groups of users, or competitors, helps you understand which way things are moving.
  • Understandable – If people can’t remember it and discuss it, it’s much harder to turn a change in the data into a change in the culture.
  • A ratio or a rate – Ratios or rates tend to be easier to act on, they are inherently comparative (see the first characteristic above) and they are good for comparing opposing factors.
  • Changes the way you behave – What will you differently based on changes in the metric?

Fig. 2 – Four reasons why you should use the One Metric That Matters – “Lean Analytics”, pp. 58-59

  • It answers the most important question you have. 
  • It forces you to draw a line in the sand.
  • It focuses the entire company.
  • It inspires a culture of experimentation.

Fig. 3 – Metrics to consider with respect to a free mobile app – “Lean Analytics”, pp. 105-106

  • Downloads – How many people have downloaded the application?
  • Customer acquisition cost – How much does it cost to get a user and to get a paying customer?
  • Launch rate – The percentage of people who download the app, actually launch it and create an account.
  • Percent of active users/players – The percentage of users who’ve launched the application and use it on a daily and monthly basis; daily active users (DAU) and monthly active users (MAU).
  • Percentage of users who pay – How many of your users pay for anything?
  • Time to first purchase – How long does it take after activation for a user to make a purchase?
  • Monthly average revenue per user – This can be taken from both purchases and watched ads.
  • Churn – How many customers have uninstalled the application or haven’t launched it in a certain time period?
  • Customer lifetime value – How much is a user worth from cradle to grave?

Fig. 4 – Common startup stages – “Lean Analytics”, pp. 153-154

  1. Empathy – Solving a problem that people care about and are willing to pay for.
  2. Stickiness – Create a good product that will solve the problem identified.
  3. Virality – Use word-of-mouth to grow your user base.
  4. Revenue – Focus more on monetizing your product.
  5. Scale – Shift from growing your business to growing your market.

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