The festive season is around the corner, and e-commerce and retail players are devising new ways to attract consumers and increase sales. As competition rises due to rising online business, e-commerce players are trying their best to corner the market pie. This has led to the rise – and requirement – of a dynamic and real-time system.
As per Gartner, e-commerce in India has registered a growth of 36 percent year-over-year. Indian e-commerce business is expected to grow to $111 billion by 2025, and the COVID-induced lockdown and government support for digitization has made this growth feasible.
A quick analysis of the e-commerce market shows there are four areas retailers should focus on to get their real-time play right:-
Adopt a Dynamic Pricing Strategy - The concept of dynamic pricing has introduced a whole new dimension to push business, courtesy of the online market. It affords sellers the opportunity to implement price changes in real-time. E-commerce has made it easier for consumers to compare prices before they buy. This allows e-tailers to watch their competition and consumer demand for competitors’ products in real-time and update their own prices to stay competitive. This dynamic pricing model – the process of continuously and frequently changing prices – is a deviation from the conventional system of fixing prices.
Dynamic pricing is partially or fully automated. Traditionally, in the pre-internet era, businesses tried multiple mechanisms to simulate dynamic pricing including rule-based systems to create what-if statements and define the relationship between rules and data. These were written specifically to an organization’s needs and lacked the flexibility to respond to a changing environment. As easy as it sounds, it’s still a difficult process in business.
Harness the Power of Data and AI - Data is a significant asset for retailers. Harnessing the power of consumer data and adopting advanced Artificial Intelligence and Machine Learning is becoming a key to mastering dynamic pricing.
This is how it works: consumers leave a trail when they shop online. By combining structured data (which includes transaction history, loyalty programs, etc.) and unstructured data (which includes product reviews, social likes, and references), intelligent pricing solutions can be created from this big data.
The accuracy of the data output depends on the quality of the input training data. It is therefore important to create and collect precise, consistent historic data to enable the ML model to glean the best information from it. Retailers should also move towards automating data collection. AI/ ML makes dynamic pricing strategy successful.
Embrace a Content Management System - Your online store requires regular, real-time updates to the product page. This is achieved by a content management system, aka CMS, which helps in fast-tracking marketing activities and promotional events. CMS also allows us to create engaging content and thereby improve e-store visibility in the online ecosystem. Store owners with negligible or low technical knowledge are able to operate it.
There are multiple CMS systems available off the shelf, and e-tailers can also build their own. The popular ones are WordPress, BigCommerce, Drupal, Sitecore, and Magento. The two important steps to fulfill when choosing a CMS are:
• Have the right keywords to appear in organic search engines – search engine optimization (SEO) is a key feature of CMS.
• Enable the right user experience by creating an easily navigable and intuitive site and also managing the same in mobile platform is imperative to boost conversion rates.
Understand User Sentiments Across Social Channels - Most consumers doing online shopping have access to multiple social media platforms like Facebook, Twitter, or Instagram. A single bad consumer experience may result in negative feedback all over social media. Here comes the importance of investing in customer sentiment analysis. By collecting data and embracing a smart insights and solutions platform that analyzes consumer behavior, buying patterns, and social sentiments, e-tailers can respond in real-time to enhance consumer loyalty.
Data-powered retailers and consumer product companies can harness the power of data to build new products and business models. For example, through the social business analytics platform of its global ‘People Data Centers’, Unilever has launched an AI-powered insights service that uses consumer data from social media, searches, and online reviews, helping it identify new trends and opportunities.
New-Age Tech and New Pricing Models – The New Business Paradigm
Playing it right and fair across these four areas on the e-commerce market will improve conversion and make e-business successful. The conventional e-commerce business will do well to transform itself into a data-powered enterprise. Retailers have new opportunities of using consumer data, but converting this to their competitive advantage can happen if they harness it with the help of AI and ML.
From the early times to the present day where new-age tech rules the roost, pricing intelligence is the name of the game. In a highly competitive world, the only means to garner customer eyeballs is to invest in new business models by understanding user sentiments and staying ahead of the curve. Or fall by the wayside!