Big Data is a trendy toy for everybody who is anybody in the highly competitive realm of eCommerce… a sophisticated toy that brings a mind-blowing ROI, when played with correctly.
Data Analytics is the process of studying Big Data. In this article let's get down to the bottom of all things related to Data Analytics development for eCommerce.
Why do you need it?
Because a jaw-dropping 35% of Amazon's sales flow from its recommendation engine algorithm that’s based on big data, and you don’t want to miss out on the power of big data analytics to drive sales.
What Is Data Analytics?
There are varying definitions of the term Data Analytics, so we provide our interpretation for you:
Data analytics is a body of scientific approaches related to qualitative and quantitative analysis that deals with gathering, cleaning, processing, and analyzing massive volumes of data to convert them into actionable insights for businesses.
In simple English, the know-how amassed by the data analytics domain allows companies to collect Big Data, format it & interpret it to improve the analytical process and produce valuable business intelligence.
Data Analysis vs. Data Analytics vs. Data Science
In order to avoid confusion and bring further clarity into the subject, let’s go over some terms that are closely related to the subject of this article and are often used interchangeably (which they should not be).
Data Analysis vs. Data Analytics
Data Analysis is a process of collecting, cleaning & processing data points.
So when we talk about analytics, it includes analysis as one of its pillars, but adds a forward, empirical dimension to past history, which is future prediction and prescription, derived through the process of analysis.
Analytics is a more general term that includes future applications of the know-how, while analysis is the process itself, focused on past facts only.
Data Analytics vs. Data Science
Data science also utilizes big data for its purposes, but it is even more forward-looking and overarching than Data Analytics.
Data Analytics allows us to answer questions about the past and make predictions about the future, while Data Science helps us to understand which questions to ask.
Whereas data analytics processes data & dwells on past trends, Data Science creates new frameworks for the future. It bases its work on predictive analytics, prototypes, custom analysis, and creating new models armed with the knowledge of past trends, indexes, peaks, and lows.
Role & Functions Of Data Analytics In eCommerce
Data analytics is the opening action item in any process optimization nowadays. You look at relevant past trends and make adjustments to improve underperforming methods and/or further amplify what's performing well.
eCommerce data analytics helps giants become even bigger. It also helps propel smaller players who know the value of big data into the top echelons of eCommerce.
Pricing & Revenue Management
Price optimization is a process many customers are blissfully unaware of.
Pricing with the help of big data, analytics & AI is becoming more advanced and more affordable at the same time. The product used to be leveraged exclusively by bigger players, like Amazon & Walmart, but now even smaller eCommerce players can take advantage of smart pricing technology.
Pricing optimization software is gaining traction because it allows companies to gain loyalty with their customers, who can rely on products to be competitively priced every time.
This algorithm allows customers to find products online with exactly the same parameters across dozens of descriptors, like size, color, dimensions, weight, style, materials used, customer reviews, etc.
If you think this is an easy task, there are 2000 shades of the color “beige” on USA websites.
Price Matching & Price Optimization
Once you have identified an item as the same product you are comparing it to, it’s time to compare the prices & adjust them according to the company's strategy.
Amazon adjusts its pricing every 2 minutes. That’s a fun fact, right? It’s literally introducing automatic by-the-minute changes to its inventory.
Smart Repricer solutions
If you are selling on Amazon, eBay, and other big platforms, customers are comparing much more than the price alone. They compare the delivery terms, fulfillment methods, product visibility, etc. This provides an opportunity for repricer solutions to help beat the competition.
Minimum Advertised Price (MAP) solutions
MAP is a pricing software solution for monitoring your resellers, so that they adhere to contracted minimal levels of pricing.
Recommendation engines are super powerful (remember, 35% of Amazon sales come from them, right?). They are used in all sorts of varieties with companies competing and doing A/B testing for the most accurate ways to name and present these sections: “People who viewed similar products also purchased X” “You may also like Y” etc.
Market Basket Analysis
Market Basket Analysis is one of the oldest tricks in the book used by data analysts in eCommerce. It allows predicting the most likely combination of products, based on past purchases. Milk and bread often go together.
Got yourself a burger? How about a Coke?
Warranty analytics works through returns, repairs, and customer claims to detect anomalies in products and predict ongoing quality issues.
This is another role for big data analytics tools in which a massive data processor helps manage an inventory, ensuring enough stock for popular items, timely deliveries, SKU controls, etc.
Use of analytics to manage inventory helps merchants avoid out of stock or oversupply situations. Monitor the market and make sure your store has everything that's trendy and topical.
This merchandising solution has a mix of assortment management and price optimization features. Competitive benchmarking software allows businesses to monitor the market and react to trends & changes accordingly.
Social listening is a tactic used by pretty much all major brands. Big Data allows sellers to pinpoint negative and positive sentiments across diverse channels and convert them into actionable insight for marketing, customer care, and even R&D.
Role Of Data Analyst
A data analyst is a person who performs data analysis. There are 3 main functions of a data analyst job:
- Clean data (a big part of the job reaching 70-80%)
- Performing mathematical calculations
- Processing, analyzing & optimizing
Big Data in its raw state is full of impurities & non-actionable insights, which need to be cleaned up. After that, the math and optimization cycle is executed to produce the desired outcome.
Types Of Data Analytics
Below are the 4 types of data analytics presented in the order of genesis from past to future applications.
Diagnostic Analytics provides answers to questions. It looks into past trends and statistics and gives a diagnosis of a situation.
Descriptive analytics also dissects the incoming data to provide a description of the past & current state of things.
The mission of prescriptive analytics is to prescribe a course of action for a company based on the data available.
Predictive analytics aims to design the optimal course of action for future company development.
7 Data Analytics Software Solutions for Savvy E-tailers
During data analytics development, multiple tools are used to achieve a cutting-edge combination of accumulated know-how in eCommerce.
Let’s review the 7 ‘must-have’ data analytics softwares for eCommerce.
Business Intelligence Software [BI]
This Microsoft product enables gathering of all data from different sources (Google analytics, social media, CRM, etc.) under one digital umbrella in order to provide actionable insight in graphs & dashboards.
Users can store, process, and share data with this BI software at just $9 per user per month.
It shares some features with Google Data Studio.
With over 27,000 companies from 130 countries in its client pool, Owox BI is a powerful marketing business intelligence software solution.
It collects data from all of your data sources so that you can get access to a plethora of insights, reports, and dashboards that provide answers and prescriptive functionality. Get all the know-how without SQL developers.
Web Analytics Software
The fundamental analytical tool for any website: eCommerce or otherwise.
It offers powerful functionality that provides an understanding of a target audience, acquisition channels, conversion, and customer behavior on a site.
The tool is free to use and is compatible with all major analytical BI software solutions. It feeds data into Data Google Studio, Google Ads, and other Google proprietary instruments, making it indispensable to the eCommerce industry.
This is a digital marketing tool that is engineered around the Search Engine Optimization concept & competitive intelligence.
Top search engine rankings are the top priority of all businesses worldwide, with extra pressure on eCommerce players. Quickly changing Google algorithms mean that keeping an eye on your website analytics is a must.
eCommerce entrepreneurs widely utilize the tools to complete an SEO audit, enhance semantic core, track position, and perform backlink audit and analytics.
Crazy egg is a tool that allows monitoring the customer journey on your website. Its main product is a technology referred to as a "heat map," which enables a business to understand: 1) how the customer moves its attention from one design element on the website to another, 2) when the customer leaves the website most often, and so on.
This heat map service provides snapshots as well as video recordings of individual user sessions. Most importantly, it also provides the option to A/B test different versions of website design elements for the best conversion.
Powerful analytical software for eCommerce that is so confident of its offering, it suggests a head-to-head comparison with Google analytics on its landing page. Kissmetrics offers two solutions, for both SaaS and eCommerce.
The eCcommerce set of services promises the ability to optimize funnels, increase sales, and integrate with Shopify, due to the highly segmented data analysis in customizable dashboards and reports.
Pricing starts at $299 a month.
Metrilo is an eCommerce analytics platform that combines the features of eCommerce analytics, CRM, email marketing, and a module on customer retention.
The Essential plan starts at $119 per month with unlimited users, but includes only an eCommerce analytics module. The Pro Plan is $199 and adds retention and CRM modules to the suite of available functions.
Using Ready-Made Solutions vs. Custom Data Analytics Development
Analytical solutions available on the market are extensive and getting more sophisticated by the minute. Many of them are available as SaaS solutions, so the pricing is fairly competitive.
When using ready-made solutions, a company gets access to a suite of predetermined settings with little chance for customization. Moreover, the same set of reports and functions is available to competitors.
On the other hand, those are tried and tested systems that cover pretty much every major KPI derived from analyzing thousands of businesses.
A custom-made solution can be developed in a way that encompasses all major functions in one suite, streamlining the functions of diverse software solutions under one digital roof.
The development of personalized data analytics also allows for unique solutions and data points that are not available in mass products.
While it may take time to develop, a customized solution is essentially a data storage repository that only your company gets access to, which is also important for bigger players who prefer to have full control of the big data they process.
Zoolatech Can Help You with Custom Data Analytics
Zoolatech specializes in eCommerce development services. Our team designs boutique high-end software development solutions across a broad spectrum of industries with a distinct focus on eCommerce retailing or e-tail.
We love implementing projects that require unorthodox decisions in the vanguard of the e-tail industry sector.
We have integrated big data analytics for eCommerce into our latest projects and would love to extend that accumulated expertise in the field to you.
Check out our retail data analytics scope of expertise before we discuss your project. No commitment. Just a consultation. Let’s talk.