Retail analytics involves making sense of data to augment decision making processes that impact profitability. Retail data collected typically comes from operations and this data can come in a structured or unstructured format. At times, internal data sets can be combined with external datasets to augment the analysis. The goal of retail analytics can be to increase sales revenues or cut cost (or both).

Lots of articles have been written about the promise of analytics but might be the only one that is dedicated to helping you evaluate if your operations are ready for it.

As a rule of thumb, by the time you have the luxury of asking this question, you are probably already too late.

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Stage

Brick & Mortar E-Commerce Level of Analytics Req.

0

1 store

<100 monthly trx Not really required

1

1-3 stores

100-5,000 monthly trx

Basic Business Intelligence Tool

2

3-10 stores

5,000-10,000 monthly trx

At least some Descriptive Analytics

3

10-15 stores

10,000-20,000 monthly trx

At least some Predictive Analytics

4 >15 stores >20,000 monthly trx

Small Team working full time on this

*Notice the bar for e-commerce is set much earlier because data is much more readily available

Stage 1

You have gone past the experimentation stage, and now you are a real business with real headaches. You can no longer talk to all your customers, and you can’t be using spreadsheets to check on the health of your business every day.

Use some form of business intelligence tool to keep you updated about how the business is doing every day.

 

Stage 2

You should be feeling out of breath at this point if you don’t have the right tools and people in place. You will need to spend most of your time hiring and giving these new hires the tools to help you manage your business. Setting KPIs and metrics only make sense if everyone can be aligned to some business metric and every manager is working towards these goals

Use these tools to help your team get the work done

 

Stage 3

The “just-in-time” mentality you used to have won’t work anymore.

What do I mean?

You used to have reports coming in to let you know it is time to restock or run promotions at this date for this stock. Not going to work at this stage. There are just too many things to worry about if you are tackling them as they come in. Set up alert systems and processes in place for contingencies when things don’t go according to plan.

Use tools that help you set alerts and plan for the future to get the work done beforehand

 

Stage 4

If you don’t have all the right analytics implementation in place, it might already be too late. This means tools for data wrangling, storage and analysis. The data is probably messy and inaccessible, and your analysts are getting fed up. At this juncture, the infrastructure is no longer a “good-to-have”.

There should be a department (maybe 2-5 people) who is taking care of this function. They should be comfortable working with data and their entire function should be to look for ways to cut cost or to increase revenue for the business.

Regardless of what statistical technique or machine learning algorithm they use, you now should have enough transaction volume to warrant the budget for such a team.

The benefits of optimisation compounds, what if…

  • 20,000 transactions they find a way to save $1 or get an extra $1 per transaction, that’s $20,000 in profits. If they can repeat that process and your business grows 5% month-on-month, that’s approximately $300,000 added to the bank account in twelve months.
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Get started early

Analytics can’t take you from zero to one, but it can help take you from one to a hundred at a much faster pace. Even if you haven’t reached a certain stage, spend some time talking internally to think about preparations for the milestones ahead.

 

Posted by:Fu Fei

Data Geek, Passionate about enabling entrepreneurship Figuring out how to gamify retail operations Twitter: @SymbolOfFlight

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