Speed ​​up your marketing plan by leveraging AI for content creation

Hear from CIOs, CTOs, and other senior executives and leaders on data and AI strategies at the Future of Work Summit on January 12, 2022. Learn more

This article was written by Ajay Mangilal Jain, Senior Partner of AI & Automation Practice at Wipro Limited

E-commerce has long been gaining popularity with private and business consumers, but the pandemic has brought an unprecedented wave of activity, even in segments that had yet to embrace online shopping. With this rapid growth and changing customer expectations for lead times and delivery, there is a growing need for direct-to-consumer brands to accelerate their marketing capabilities. At the center of this trend is the need for content, which now needs to be scaled across different platforms. and segments quickly and intelligently. However, this process is very demanding and the creation of effective content for multiple platforms, including e-commerce, is almost impossible without a suitable infrastructure of artificial intelligence (AI) and machine learning (ML).

When AI succeeds, so does content and content creation

To influence people, companies have to say something smart and relevant to the customer. Quality content resonates, creates relevance and influences behavior. Creating this type of content requires analyzing data across multiple platforms, assessing response rates to different mediums, and delving into customer sentiment and engagement. Unfortunately, all of this takes time, a lot of time.

AI and ML have the potential to accelerate this process. AI has the ability to analyze large amounts of data and make recommendations on what content is most likely to elicit the desired response. This automated analysis helps companies generate meaningful content and expand content development to be perfectly suited to different platforms and market segments.

Historically, direct-to-consumer brands have relied on AI and ML primarily for social listening and insights. While some social platforms have introduced in-app purchases, the majority of consumers still shop through traditional channels and their use of social media is focused on product research. This makes social media a great place to influence consumer behavior and capture data. AI and ML consolidate data from these platforms – analyzing context, relevance, sentiment, and feedback to determine what drives the consumer and predict the best performing content for each scenario.

Using AI / ML to expand e-commerce

AI and ML can also play a key role in e-commerce content development. With more and more online shopping, new ways of meeting demand have emerged. This has introduced new complexities for content marketers as direct-to-consumer businesses seek to expand their presence into other commerce platforms and channels. By leveraging AI and ML, businesses can overcome these complexities while increasing their visibility across platforms and gaining insights that ultimately drive growth.

Take the case of an international brand of chocolate. In early 2019, the company had a commercial presence both on its own website and on a leading e-commerce website, where it hosted a number of product pages to address various segments and test different keywords and images. The marketing team used the platform to analyze the most successful pages and determine which items consumers found most relevant. In addition, the team had to determine which research data was also the most relevant.

The brand wanted to expand its online sales presence to other retail websites and social platforms. This expansion, while promising, would essentially “trap” consumer behavior and sentiment data from each outlet within the respective platform. The challenge would then become how to best analyze what resonated with the audience of each platform and continue to create effective “feel-good” content that sets the company apart from its competitors.

By leveraging AI and ML, the chocolate brand was able to capture and combine data from its e-commerce channels, own product sites, and all new platforms. The ability, through AI, to aggregate and analyze content for every product, segment and platform has enabled the company to grow rapidly and create the most relevant content for every digital property. Additionally, the increased efficiency accelerated the creation of content that resonated with target consumers, while also leading to increased page visits and sales.

While AI and ML are often seen as a technology with limited applications outside of dry data analysis, they can actually be used to fuel creativity. These tools allow businesses to analyze branded content from multiple systems, build bridges between platforms, improve content creation, as well as empower their marketing teams to create and deliver. scale the most relevant content across multiple platforms. Incorporating AI into a marketing strategy helps brands that speak directly to consumers quickly identify content that resonates, creates relevance, and influences behavior. All of these features provide businesses with the ability to scale quickly and respond to changes in sentiment in real time.

Ajay Mangilal Jain is a senior partner of the AI ​​and automation practice at Wipro Limited

Data makers

Welcome to the VentureBeat community!

DataDecisionMakers is the place where experts, including data technicians, can share data-related ideas and innovations.

If you’re interested in learning more about cutting-edge ideas and up-to-date information, best practices, and the future of data and data technology, join us at DataDecisionMakers.

You might even consider contributing your own article!

Read more about DataDecisionMakers

Source link

Jenny T. Curlee