In my previous article, I suggested a minimalist approach to digital analytics known as Minimum Viable Analytics (MVA). This approach focuses on implementing essential analytics features that provide immediate value without overwhelming resources or requiring a specialist’s expertise.
Why a minimalist approach?
I recommend the minimalist approach for most companies that don’t have a dedicated analytics specialist on their team.
Without specialist skills, advanced analytics implementations are often forgotten or become overwhelming. A simple implementation is more straightforward and helpful, allowing teams to focus on actionable insights rather than getting lost in data.
For example, a small online retail store might start with basic metrics like page views, bounces, and conversion rates. These basic metrics can provide immediate insights into customer behaviour and website performance without complex tools or detailed analysis.
Who can benefit from MVA?
MVA offers a minimalist approach to digital analytics. It enables fast, data-driven decision-making without the complexities and costs associated with extensive data infrastructures. This approach is handy for:
- Startups: New businesses need to become data-driven quickly and efficiently without a significant upfront investment. MVA allows early-stage startups to gather essential insights to drive growth and strategic decisions. At this stage, a full-scale analytics team and expensive tools are unnecessary.
- Small to medium-sized businesses (SMBs): These businesses often have limited resources and need to maximise the value of their data. An MVA helps small businesses implement easy-to-use analytics to understand customer behaviour, optimise marketing efforts, and improve overall business operations.
- Enterprises transitioning to a new platform: Large companies looking to migrate to a new analytics platform can use MVA as a valuable first step. It provides a robust framework for tracking key metrics during the transition period.
- Enterprises streamlining existing analytics: Even established companies can benefit from MVA when they need to streamline their existing analytics processes. By focusing on the most important metrics and removing unnecessary complexity, enterprises can make their analytics more efficient and actionable.
In summary, a minimum viable analytics implementation can be used by most companies, not only in their early stages. But of course, there will be a time for building something more advanced.
Is it time for something more advanced?
But when do you know it is time to build something more advanced?
The right approach to digital analytics will depend on the specific needs of your business.
Here are some signs that the minimalist approach and an MVA might not be enough for your business:
Increased traffic and conversions
As your website grows and attracts more traffic, your data needs will also grow. This growth is often connected with increases in the marketing budget and rising expectations.
For instance, an e-commerce site that starts gaining thousands of visitors and hundreds of conversions daily will need more than just basic metrics to understand user engagement and sales.
When traffic increases, also more granular data starts to be interesting.
Difficulty to make data-driven decisions
If you’re finding it more and more challenging to make informed decisions based on your data, it may be time to build something more complex.
For example, an online business struggling to understand why sales fluctuate despite stable traffic might need to dive deeper into web analytics data.
They might, for example, need to analyse the specific actions users take before making a purchase or abandoning their cart.
Need for advanced analysis
You may need to track more data to implement advanced analytics like predictive analytics.
This helps you understand your users and their behaviour better.
For example, a subscription service might use predictive analytics to forecast churn rates and identify at-risk customers.
This allows the business to proactively retain these customers, such as offering personalised discounts or enhanced support.
Integration with other systems
If you’re looking to integrate your analytics platform with other data sources, such as your CRM or marketing automation platform, you need a more advanced implementation.
For instance, a business that wants to track the full customer journey from initial contact through post-purchase follow-up must integrate website analytics with CRM data.
This integration enables more personalised marketing efforts and a better understanding of customer lifetime value.
Ensuring a positive ROI
It’s important to have a positive return on investment (ROI) when building something more complex than MVA.
Advanced analytics implementations are resource-intensive. They require more time, money, and expertise. Therefore, you must evaluate the benefits of insights gained and the costs involved.
You could, for example, consider how many incremental conversions you need to make the investment profitable. As the traffic and conversions increase, a smaller percentual increase will be profitable.
For example, a business planning to implement predictive analytics should consider whether the insights gained will significantly improve customer retention and sales. This could justify the additional investment.
Tracking more data is just part of the solution
Also, in this case, you should remember that analytics implementation and data collection are just one part of the equation.
Usually, not collecting enough data isn’t the critical issue. More likely, the data collected with an MVA setup was not analysed or used for decision-making.
For example, a small business might track enough data to understand its customer demographics and purchasing patterns but fail to use this data effectively.
This is why having a data-driven culture in your organisation is essential. Without this, investing in a more advanced digital analytics implementation rarely makes sense.