situation and forecasts for e-commerce

What future for e-commerce? Faced with the pandemic, globalization, new consumer expectations, namely with regard to environmental impact and the web2store, retail is changing. Artificial intelligence tools designed to address these challenges exist, but have professionals adopted them? Adoption, deployment, expectations and obstacles are at the heart of this new study proposed by OpenStudio.

In fact, it is to answer these questions that OpenStudio is delivering the results of a study carried out with 132 retailers from all sectors of activity in September 2021. To Cédric Sibaud, Associate Director of OpenStudio and e-commerce expert:

“Artificial Intelligence has already become essential for the big names in e-commerce, it will become mandatory for all commercial websites, regardless of size. Therefore, retailers have every interest in taking an interest as soon as possible in this technology, which is becoming more democratic and opens the door to great opportunities.”

Discover the 10 key points of this survey below, which you can also download HERE.

Also find OpenStudio in issue 5 of ActuIA, the artificial intelligence magazine currently in digital version and on newsstands!

1 – Retailers almost unanimously (98%) believe AI could improve their e-commerce platform, including 62.5% significantly

2 – Retailers’ expectations regarding AI are very high: turnover and time savings, the 1st goals
Strong and/or priority expectations are:

  • save time through automation: 84%
  • facilitate decision making with real-time analytics: 83%
  • increase revenue: 81%.

If we only take into account “priority” responses, increasing turnover is the first objective attributed to AI for 47% of retailers, followed by improving customer relationships by 43%.

3 – 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. Top 8 positions for which they consider AI a priority and/or useful:

  • update, manage and enrich customer databases: 90%
  • automate order preparation and shipping: 89.7%
  • detect fraud and anomalies/secure payments: 89.7%
  • understand/model/predict the behavior of Internet users (purchases, etc.): 89.2%
  • sync catalogs across all third-party apps (ERP, marketing tools, etc.): 88.9%
  • forecast sales and manage inventory: 86.7%
  • updating catalogs and prices in real time: 85.4%
  • streamline the customer journey (web2store): 85.2%.

4 – Top 5 solutions deployed: monitoring, Big Data processing, analysis and forecasting
Competitive pressure, volume of data to be processed and multiplicity of its sources, need to analyze this data to take advantage of it, retailers had to invest to deploy AI solutions, the top 5 are for:

  • provide competitive intelligence: 36%
  • process Big Data: 34%
  • analysis: 32%
  • tied: real-time predictive: 32%
  • enrich customer data (cross-checking with external data such as social networks): 31%.

5 – Intentions to deploy AI solutions in 18 months: Big Data and chatbot/voicebot
Data continues to be a major concern for retailers, but they also intend to equip themselves with automation tools for customer relationships. The first 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-referenced with external data such as social networks): 34.5%.

6 – 18-month deployment status: Big Data processing is essential
Among the AI ​​solutions already deployed and those to come on the 18th, the first 4 that retailers will have will be:

  • AI to Process Big Data: 72%
  • AI to enrich customer data (cross-referenced with external data such as social networks): 65.5%
  • chatbot/voicebot: 63.5%
  • AI for analysis: 63%.

7 – Top 3 increases: chatbot/voicebot by over 124%
All AI tools will benefit from the investments, the 3 biggest increases expected in the next 18 months are:

  • chatbot/voicebot: +124%
  • AI for personalization of marketing campaigns: +114.5%
  • AI to enrich customer data (cross-referenced with external data such as social networks): +111%.

8 – The first 4 obstacles to the development of AI in e-commerce: ethics and costs
AI raises more and more ethical questions and they seem to be the first brake, tied to the cost of its implementation. The first 4 barriers identified by retailers are:

  • ethical issues raised by the use of AI: 33%
  • tied: the cost of implementing AI solutions: 33%
  • the difficulty of measuring/quantifying AI contributions: 32%
  • complexity to implement AI solutions: 31%.

9 – Retailers committed to good practices of “responsible digital” in e-commerce
Retailers aware of the issue of responsible e-commerce have already implemented concrete measures to reduce the environmental footprint of their activity, the first 3 are:

  • store data in green datacenters: 40%
  • offer customers offsetting the carbon emissions emitted by their orders: 39%
  • optimize the site using an eco-design approach: 36%.

The vast majority of retailers put these topics on the agenda, with the first 3 being considered:

  • website optimization in an eco-design approach: 48% (36% have already implemented this measure)
  • the use of open source AI models: 47% (already implemented: 34.5%)
  • tied at 47%: hosting the site in a green center (already implemented: 33%).

10 – AI is an asset to control the environmental impact of e-commerce
AI is a valuable ally for retailers, including for controlling the environmental impact of e-commerce to:

  • limit customer feedback thanks to predictive: 75%
  • rationalize packaging: 72%
  • tied: reduce carbon footprint by optimizing delivery routes: 72%.

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