Updated: Sep 21
When we ask business owners what their growth strategy is.
We often hear ‘10% increase in sales’
But when we dig deeper and ask how they are going to achieve this there isn’t really a plan in place.
Acquiring more customers, attracting new audiences, attracting more valuable customers
Keep existing customers loyal
Increasing frequency and spend to grow new ones
Engaging and incentivising others to repurchase
Do you know where to focus to get the greatest return?
No one has a crystal ball to predict the future but using data and insight can help your planning.
Building a growth strategy with a data mindset would enable you to determine where to focus. By identifying and quantifying each opportunity and to make informed decisions to prioritise where to focus
Data is much more available nowadays with more businesses embarking on digital transformation, but are you using it to support strategic decision making?
The data nirvana is to be able to access all of your data in one place, machine learning or AI is continuously running to analyse the data to identify and recommend opportunities and areas to optimise at a click of a button.
A bit like Google Ads but for the whole of your business.
In reality, the average business is a long way off this. However, there are still lots of ways in which to still find opportunities through using data to give you a competitive advantage whilst building up capability over time.
Having successfully worked with business owners and SME’s we find that by conducting an 'exploratory data analysis 'of your business will move you forward in an agile way, identify new opportunities quickly, identify weakness in the data and to demonstrate the value of investing in infrastructure and technology.
We typically see that businesses have pockets of analysis undertaken to address different tasks across the organisation ie marketing channel CPA, but rarely are they looking at it at an organisational level or at the cross relationships between different areas ie loyalty of customer by acquisition channel.
This is often due to missing operational integration between different systems and a lack of a single customer view, with the development likely to fall into a longer-term development plan and require significant investment.
One way to get around this is to create an analytical single customer view either a static snapshot or by using tools such as funnel or Supermetrics to pull different data sources together to be able to report in real-time.
Initially, I prefer to work with a static snapshot as often the data will need to be cleaned to identify duplicate records and remove outliers and test data that will potentially skew any analysis.
This can often be insightful in its own right and can be used to clean up and group together data within the operational systems and then use the reporting integration tools to pull together the data for on-going reports analysis.
The knowledge gained about your data can also be used as a blueprint for building an SCV using integration and ETL tools like Talend or DXClover and building a data and analytics warehouse in SnowFlake or Google BigQuery.
Please note that data quality is a key part to having the useful insight to make decisions on an on-going basis and this stage often highlights further areas of investigation as to how the data is captured on-line, short cuts that have been made by agents at the point of data collection or poor data management.
Once the analytical single customer view is in place, it will be possible to conduct an ‘exploratory data analysis’ which means looking at trends over time, distribution of spend, frequency of purchase, length of relationship, correlations between spend & customer profiles, customer loyalty & acquisition media and the ability to investigate different hypothesis within the business.
This approach can be a great way to look at your business in a new way and an opportunity to identify macro impacts that may have happened within the business such as business acquisitions or changes to T&Cs.
But often it's the first time the business has seen an analysis of the customer in detail rather than product sales. By looking at customer lifetime value, the different life stages of a customer and the impact of marketing on customer value will start to identify new opportunities.
One of the biggest benefits is to be able to fully understand the sales funnel at a macro level and provide the ability to break down the ‘10% growth’ figure.
This analysis will become invaluable to the businesses to build strategies around, to start quantifying the potential impact they will bring to achieve the business growth ambitions and shaping what you need your on-going data strategy to be.
We find one of the biggest barriers to using data to support strategic decision making is knowing where to start.
We can help demystify what you need to do.
We always start with a free discovery call to establish what your focus is and an opportunity to pick the brains of one of our experts.