One of my first professional experiences back in the early 2010s was as a Marketing Operator where I performed data analysis on an e-Commerce that sold online coupons like Groupon. In Venezuela we had very limited access to any international currency, therefore we had very basic software tools for analysis.

We worked with excel and our database. I will share my experience on how we used analysis to generate sales and better value.

What data should you analyze on e-commerce

Classical marketing response: It depends! I use data relevant for the purchase that generates value for the customer.

I worked in e-commerce with different product categories. As a result, I used to select the type and category of the item, date, price, quantity, age of the customer, vendor location, and discount value.

The first requirement working with data is to have a curious mind, play around with different statistical techniques, and elaborate hypotheses. Consequently, share them with your sales team and dare to try them.

I was lucky to have an amazing boss who would be open to trying new stuff and an amazing sales team that would trust our data. Therefore many of our results were amazing!

Obstacles in analyzing data

In my experience, I think that there are three common problems that are, the know-how of using technology & statistics, overthinking, and finally being afraid to share a finding that might look absurd out of fear of being made fun off.

For the know-how people really need to know what they are doing, luckily there are amazing educational resources out there. For example, I learned basic Python using Coursera.

There are amazing free resources in sites like Google academy, SEMrush academy, and Salesforce’s trailhead where you can learn analytics, marketing tactics, and even about artificial intelligence.

Learning Python, or other tools can enable you to have endless data analysis capability. But I believe that nothing beats the human mind’s inspiration and curiosity behind them. So trust your gut and let the tools work for you and not you for them.

Secondly, dare to fail. Propose ideas and alternatives, you can make tests in controlled settings before going full market, but if you don’t speak up all those wonderful ideas that data is telling you will be wasted.

Interesting findings examples of data analysis on an e-Commerce

I used basic data analysis on excel, including regressions, descriptive statistics, and statistical tests. However, that allowed us to find several interesting things:

  1. Finding top vendors and locations.
  2. Finding seasonality attributes on products.
  3. Price sensibility analysis.
  4. Prioritize promotions promoted on marketing channels that yielded higher returns.
  5. Define location for promotions on the website.
  6. Design promotion packages for special holidays.

Data allows us to offer value more efficiently to your customers and makes the life of your coworkers easier. Therefore, dare to be curious, learn, and try new things, results will be exciting!

Data analysis can determine strategies in pricing, content writing, and positioning.
Data analysis can determine strategies in pricing, content writing, and positioning. Source of image

To close up I leave you with a quote of David Ogilvy “Don’t bunt. Aim out of the ballpark.” In conclusion, go get some home runs!

Don’t forget to check last week’s post transforming data points into data insights. Also if you have any questions please leave a comment below!

Photo by Campaign Creators on Unsplash