What exactly does success mean for a startup? There are many definitions offered by academicians, consultants, investors, accelerators, and of course, founders themselves. Opinions and advice cover everything, from market share and profitability to valuation and organisational purpose.
For example, success for startups in the NetApp Excellerator is defined as any or all of three things: getting customers, raising investment, and making significant improvements in their product offering. For the Pitney-Bowes accelerator, a startup’s success is based on how well they are able to take their products to market, and build true value for their customers.
In the case of global accelerator TechStars, startup success could even mean just staying alive and continuing to live to fight another day. Success includes perseverance in the face of adversity and even misery, just to chase dreams and make them come true. Winning awards, getting media recognition, and becoming industry thought-leaders are other measures of a startup’s success.
Investment firm Andressen-Horowitz has compiled a list of 16 startup metrics. For example, financial metrics track bookings and revenue. Recurring revenue, gross merchandise revenue, gross profit and contract value measure the health of the company.
From the customer side, the metrics to track include Life Time Value (LTV), Customer Acquisition Cost (CAC), periodic churn, referral rates, and customer satisfaction. From the product side, it is important to measure level of engagement and frequency of interaction, and types of heavily used features.
Marketing metrics should include conversion rates and brand recall across acquisition channels, based on cohort analysis (eg. social media, email campaigns, search engine optimisation). Sales metrics cover the performance of sales teams across market segments and geographies, and is broken down into number of visits, demos, trials, calls, online interaction, expended effort, resources deployed, and closed deals.
An important operational metric is the cash burn rate; internal metrics include employee satisfaction and churn rates. All the above metrics should also be visualised in dashboard forms and shared with the core team, so that everyone is aligned with the progress of the company.
A startup can be viewed as a high-performance learning organisation – which opens up the analysis to two kinds of metrics, related to productivity and innovation. The startup journey involves finding product-market fit, designing the right features, devising end-to-end customer solutions, and fine-tuning the right business model.
Accordingly, drawing on the earlier analysis in this article, there are five key types of metrics entrepreneurs should add to their performance dashboards: activity, process, knowledge, people and business.
These are a necessary, but not sufficient, reflection of traction – also described as technology metrics or even vanity metrics. Measures such as web traffic, app downloads, footfalls and online interactivity fall in this category.
If you have low performance in these basic ‘entry-level’ metrics, you better go back to the drawing board and start over again. But even high performance in this phase is only the first step towards success. You may be getting lots of traffic and delivering good value to your customers (for example free content), but you need to capture some of that value yourself.
This is where the action really begins, and affects your inbound, outbound or back-end processes. For example, are you able to improve a certain core business process or activity for your customers, or for your business model?
This could be lowering costs of acquisition, higher efficiency in marketing, better price comparison services, higher sales rates, and so on. These should be tied to specific problems and pain points of your B2C or B2B target consumers.
This is where you are actually building best practices (as well as worst practices to avoid!) in your startup processes, gleaning valuable customer insights and profiles, filing patents, refining checklists for engagement of different customer segments, and so on.
As explained by Eric Ries in his Lean Startup methodology, startups are companies that are ‘specifically geared to product and institution building in a context of extreme uncertainty, based on innovation accounting and build-measure-learn cycles.’
Knowledge metrics are focused on validated learning from customers about business prospects (the most vital function of a startup). Startups should become adept at not just knowing their domain but learning and experimenting efficiently in this domain. The repository of tested and validated hypotheses – and the speed of crafting such quality learnings - are part of the success fabric of a startup, particularly in a hyper-competitive ecosystem.
Interestingly, a big part of measurement also involves tracking and monitoring failure rates and understanding how to miminise this loss. A fast-moving, interconnected and complex world calls for increasing knowledge and skills in experimentation, iteration, self-reflection and decision-making. Frequent mistakes will alternate with occasional moments of triumph.
Tracking failures also includes reducing the causes of failures in the first place. This includes calibrating the number and quality of experiments and pilot projects, connecting failures to the relevant parts of the business model, and ensuring that mistakes don’t get repeated again. Mistakes should be tracked to sources such as system design, tech architecture, and business decisions.
These are semi-quantitative metrics which assess the level of satisfaction of your customers, employees, managers and business partners. How well are you performing in the LIFE metric (Little Innovation From Everyone)? How are you measuring progress against attrition and poaching? What is the empowerment and aspiration level of your team?
External metrics on the people side include how satisfied your customers are with the product performance, price points, and after-sales service. In ecosystem-based innovation, the level of comfort and trust among your channel partners is also an important people metric.
At this stage, it is also important to track qualitative measures, such as stories or anecdotes. Stories can be about outstanding performers on the team, how crises were effectively avoided, or how difficult customers were dealt with. Customer testimonials in the form of short quotes, all the way to full-fledged case studies, go a long way in building confidence among employees, investors and future customers.
These are some of the most important metrics a startup must measure itself up against. Investors, especially, will look at customer retention rates, up-selling and cross-selling, profit margins, and competitive moats. These measures are cascaded from the previous types of metrics.
There is no end of advice startups will get on such metrics, and this may seem bewildering at first – but clarity will emerge once you categorise metrics and expectations by sector. For example, retail sector startups (such as grocery delivery) will require large investments upfront even before launch, B2B enterprise sector startups may also need relatively large investments early on. On the other hand, B2C digital startups may be able to show some validation and revenues even before needing funding.
In sum, having a unified view of startup metrics helps track momentum and set the right expectations. It also calibrates progress against competing startups and market incumbents. Calculating market share helps map the startup’s position into categories like challenger, beachhead, or market leader.
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To learn more on how to take your startup to the next level, visit Vodafone’s Ready Startup microsite.