The onward march and transformation of ecommerce
This is the third article in a series that seeks to provide leading insights into the rapid transformation of ecommerce. In this article we provide some recommendations on what to consider in order to be able to deliver an exceptional ecommerce shopping experience.
In the first two articles we touched on the underlying trends that are transforming the world of ecommerce and how consumer expectation keeps rising at an inexorable rate. In this article we delve into what it takes to keep ahead of the pack and to provide a shopping experience that sets you apart from your competitors. To deliver an approach that differentiates you, not only in terms of customer experience, but also distinguishes you as a compelling and highly relevant brand in the eyes of the shopper.
Customer journeys provide the foundation
The notion of customer journeys has been around for some time. I am sure we have all, at some point, worked on a customer journey plan. The challenge is in the implementation, as this requires different departments and teams to align their efforts and to act and execute in a highly synergistic and consistent way across every consumer engagement and touch point.
The traditional thinking was to develop a single master record that all teams would use to define best next actions. This was the foundation of the CRM system and the notion of 1:1 marketing. However, the data is all historic, it reflects previous behavior, but it may not reflect your behavior now, in the moment. Taking this traditional approach opens up the very real possibility of the wrong interpretation of real-time shopper intent and hence the likelihood of delivering an irrelevant experience.
The rise and rise of Data Science
What is really required is the application of Data Science. Data Science is the art of extracting and applying actionable insights from your data, both historical but also more importantly in real-time. It uses scientific methodologies to do this — including workflows, models, algorithms and systems.
“Information is the oil of the 21st century, and analytics is the combustion engine.” Peter Sondergaard, Senior Vice President at Gartner
Retailers and brands that are able to develop a data strategy that is geared directly to unearthing and identifying real-time shopper intent will be in a far better position to deliver the right shopper experience, whilst also delivering on their goals. This we refer to as Smart Data. It is the analysis of this Smart Data that delivers the actionable insights that can elevate business performance.
Data Science is tasked with knowing what data to capture, how to transform it, how to analyse it and how the corresponding results can be delivered in a way that makes them easily actionable, whether through automation or manual curation. By taking an integrated approach to a single data lake and then using this to establish a single “Intelligence layer”, organizations can inform cross-functional working and achieve true competitive advantage in online shopping experiences.
- Marketing will know where to focus their efforts on finding and motivating the right traffic for their ecommerce site and to integrate the arrival of this traffic onto the site in a seamless and fully aligned way with their brand promise.
- Merchandise Planners will be able to predict what items will be popular and what the likely demand will be, and how various attributes such as price will influence overall conversion.
- Visual Merchandisers will know the likely impact of all the individual levers they can apply to their ecommerce site experience to influence shopper behaviour and how they can be combined to deliver the best results for everyone.
In summary, Data Science has the ability to enable highly effective cross-departmental cooperation, based on insights that are accurate and actionable. This enables the best possible outcomes to be delivered that meet both the expectations of the shopper whilst also meeting the commercial goals of the organisation. Ecommerce success for a brand or retailer relies on managing this balance in an environment where the information is constantly changing. Without a structured Smart Data and Machine Learning approach, decisions revert to being made on historical data, narrow data points or sometimes gut feeling alone, resulting in conflicts and misalignment across teams.
“Consumer data will be the biggest differentiator in the next two to three years. Whoever unlocks the reams of data and uses it strategically will win.” Angela Ahrendts, Senior VP of Retail at Apple
The future of ecommerce and the increasing development of Data Science are very closely tied.
Please feel free to reach out to me directly on email@example.com if you have any questions. Alternatively, watch our video to discover how Attraqt is transforming the ecommerce experience for the world’s best retailers.