What future for e-commerce? Faced with the pandemic, globalization, new consumer expectations, especially regarding the environmental impact and the web2store, retail is evolving. Artificial intelligence tools developed to meet these challenges exist, but have professionals taken them up? Adoption, deployment, expectations and obstacles are at the heart of this new study proposed by OpenStudio.
To answer these questions, OpenStudio has released the results of a study conducted with 132 retailers from all sectors of activity in September 2021. For Cédric Sibaud, Associate Director of OpenStudio and e-commerce expert:
“Artificial Intelligence has already become indispensable for the big names in e-commerce, and it will become a must for all merchant sites, regardless of their size. It is therefore in the interest of retailers to take an interest in this technology as soon as possible, as it is becoming more and more democratic and opens the door to great opportunities.
Discover below the 10 key points of this survey, which you can also download HERE .
You can also find OpenStudio in the issue 5 ofActuIA, the magazine of artificial intelligencecurrently in digital version and in newsstands!
1 – Almost all retailers (98%) believe that AI could improve their e-commerce platform, 62.5% of them significantly
2 – Retailers’ expectations of AI are very high: Sales and time saving, the 1st objectives
The strong and/or priority expectations are :
- save time through automation: 84
- facilitate decision making through real-time analytics: 83
- increase sales: 81%.
If we take into account only the “priority” answers, the increase of the turnover is the first objective assigned to AI for 47% of retailers followed by the improvement of the customer relationship at 43%.
3 – The top 8 priority and/or useful AI solutions: manage data, automate and secure payments
For retailers, AI is a real opportunity that will improve the performance of their e-commerce platform. The top 8 items for which they believe AI is a priority and/or useful:
- update, manage & enrich customer databases: 90
- automate order preparation and shipping: 89.7
- detect fraud & anomalies/secure payments: 89.7
- understand/model/predict Internet user behaviour (purchases, etc.): 89.2
- synchronize catalogs with all third-party applications (ERP, marketing tools, etc.): 88.9
- forecast sales and manage inventory: 86.7
- update catalogues and pricing in real time: 85.4
- make the customer journey more fluid (web2store): 85.2
4 – Top 5 solutions deployed: watch, process Big Data, analyze and predict.
Competitive pressure, volume of data to process and multitude of its sources, need to analyze this data to take advantage of it, retailers had to invest in order to deploy AI solutions, the top 5 are for :
- ensure competitive intelligence: 36
- process Big Data: 34
- analytics: 32
- ex-aequo: real-time predictive: 32
- enriching customer data (cross-referencing with external data such as social networks): 31%.
5 – AI solutions deployment intentions within 18 months: Big Data and chatbot/voicebot
Data remains the major concern of retailers but they also intend to equip themselves with automation tools for customer relations. The top three solutions they plan to implement in the next 18 months:
- AI to process Big Data: 38
- chatbot/voicebot: 35
- AI to enrich customer data (cross-referencing with external data such as social networks): 34.5
6 – Deployment status in 18 months: Big Data processing is a must
Between the AI solutions already deployed and those to come in the 18, the top 4 that retailers will have will be:
- AI to process Big Data: 72
- AI to enrich customer data (cross-referencing with external data such as social networks): 65.5
- chatbot / voicebot: 63.5
- AI for analytics: 63%.
7 – The top 3 fastest growing: chatbot/voicebot up +124%.
All AI tools will benefit from investments, the top 3 expected to grow over the next 18 months are:
- chatbot/voicebot: + 124
- AI for marketing campaign personalization: + 114.5
- AI to enrich customer data (cross-referencing with external data such as social networks): +111%.
8 – The top 4 obstacles to the development of AI in e-commerce: ethics and costs
AI raises more and more ethical questions and they appear as the first obstacle, ex-aequo with the cost of its deployment. The first 4 obstacles identified by retailers are :
- ethical issues raised by the use of AI: 33
- tie: the cost of implementing AI solutions: 33
- the difficulty to measure/quantify the benefits of AI: 32
- The complexity of implementing AI solutions: 31%.
9 – Retailers committed to good “responsible digital” practices in e-commerce
Retailers who are aware of the issue of responsible e-commerce have already implemented concrete measures to reduce the environmental footprint of their business, the first 3 being :
- storing data in eco-datacenters: 40
- offer customers the opportunity to offset the carbon emissions emitted by their orders: 39
- optimize the website with an eco-design approach: 36%.
The vast majority of retailers have put these topics on the agenda, the top 3 that are under consideration:
- optimising the website in an eco-design approach: 48% (36% have already implemented this measure)
- the use of open source AI models: 47% (already implemented: 34.5%)
- ex-aequo at 47%: hosting the site in a green center (already implemented: 33%).
10 – AI an asset to control the environmental impact of e-commerce
AI is a valuable ally for retailers, including to control the environmental impact of e-commerce to :
- limiting customer returns through predictive analysis: 75
- rationalize packaging: 72
- ex-aequo: reducing the carbon footprint by optimizing delivery routes: 72%.