Go back to Blog's hub Blog   |   tags:  

How to Boost E-Commerce Sales With Data Analytics

Written by Harry Dix  | 

Share
How to Boost E-Commerce Sales With Data Analytics

Recent events have accelerated consumer demand and transformed the global e-commerce sector — including a major boom in overall market size.

Previously, e-commerce mostly encompassed smaller online shops connected to brick-and-mortar stores. Today, it’s a highly competitive space dominated by large e-commerce marketplaces. brands must utilize e-commerce platforms to sell their goods and are increasingly reliant on data for tracking consumer trends and market developments in order to maximize their revenue.

The data collection part of the equation is fairly easy. However, drawing actionable insights from the ever-increasing amounts of data is where the real challenge lies — and where the competitive advantages can be found.

Step 1: Maximize Sales and Existing Revenue

To rise above the competition, strive to maximize performance. The most effective way to do so is by empowering your retailers with data.

However, while a monthly pdf export or spreadsheet of sales and consumer data was once sufficient, today’s massively competitive landscape requires retail brands to access daily actionable information for prompt reactions to changing consumer trends, increased or decreased product demand, and the like.

Step 2: Create an Entirely New Revenue Stream

Not only can the data you already collect help maximize your existing business model, increase brand partner loyalty, and attract new brand partners, it also can provide an entirely new revenue stream: by creating tiered analytics access.

For example, imagine that you collect data about consumer behavior related to your website or marketplace: where they go, what they save as desired items, what they buy, and so on. All this information can be divided into data tiers, with one tier provided to retail brands for free (e.g., basic data insights) and the other provided for an additional fee (e.g., advanced, more detailed data insights).

By creating ‘free and paid tiers within your data offering as described, you can tap into a new revenue stream, all the while giving your brands the ability to improve their performance. The free data tier forms your brands’ entry point to analytics, and the paid data tier lets them expand into in-depth sales and consumer behavior analyses. And as that data helps them streamline their business, their desire to access more data increases.

Your final data design would then depend on your specific data strategy and e-commerce structure.

The Tools to Get It Done

Of course, different analytics use cases need different analytics solutions. For example, if the use case is to supply retail brands and partners with daily actionable information on a variety of products and product categories, an embedded analytics solution is recommended. Some of the key features of such a solution should include:

  • Scalable architecture: The solution is able to grow in line with business growth and customer demand.
  • Self-service capabilities: Customers gain the ability to easily access analytics insights.
  • Airtight data security: Each customer’s data remains separate and secure.
  • Rich customization options: Customers are able to have a seamless embedded analytics experience.
  • Efficient deployment: The solution is quickly rolled out and deployed in the most convenient way for your business.

During your search for an analytics solution, here are additional questions to consider:

  • Build or buy: Should we develop an in-house analytics solution embedded into our product, or should we purchase an embedded analytics solution from a specialized data analytics provider?
  • Scalability: Will the solution scale with our future growth plans?
  • Self-service with drag-and-drop visualization: Can our customers’ end users create their own analytics visualizations or dashboards without prior technical knowledge?
  • Security and privacy: Who has access to what data and how is the data of different customers kept separate?
  • Predictable pricing: Is the pricing model transparent, and how does it affect current and future profitability?

Ready to Learn More?

Are you ready to learn more about embedded analytics and the benefits it can bring to your e-commerce business? Read more about our e-commerce formula for success by downloading our guide to driving e-commerce success with analytics e-book. It digs into the details of how to maximize sales and develop a new revenue stream with your data. Alternatively, continue to the e-commerce platform overview page to discover the GoodData platform and its full feature set.

Why not try our 30-day free trial?

Fully managed, embedded analytics platform. Get instant access — no installation or credit card required.

Get started

Written by Harry Dix  | 

Share
Go back to Blog's hub Blog   |   tags: