Using AI for Onboarding New Products

The minute your company finds onboarding new products has become far too complex and time-consuming is the minute you need to improve your process. Today many retailers and eTailers use artificial intelligence (AI) such as machine learning, natural language processing, and computer vision to adopt automated approaches to streamline the many annoying aspects of product onboarding. Here we explore how using AI for onboarding new products makes the process a breeze.

1. Increased speed of time-to-market

AI increases time to market using automated steps that eliminate time-consuming manual processes. For example, you can use AI to analyze product information and automatically populate fields with relevant information.

Instead of someone depending on manual searches of complex spreadsheets and spec sheets, AI understands the required information and drops it into templated sheets to ensure all essential attributes and data are placed correctly.

Through automation, you reduce the risk of errors and manual corrections. You also improve productivity and efficiency in the onboarding process. AI also automatically categorizes products based on attributes. This enables you to customize product information based on the unique formatting requirements of each marketplace.

Finally, AI makes it easier to create product descriptions by searching for and comparing similar online product data to improve accuracy and description content.

All these capabilities reduce the number of steps in the onboarding process, creating a faster time to market. As a result, you generate revenue more quickly for new products while also beating out the competition.

2. Improved accuracies

AI uses machine learning to improve constantly. For example, Pimberly uses deep learning technology that enables our AI to learn by example. As a result, users also learn from past onboarding processes and can confidently use AI to predict product categorization, pricing, and critical attributes.

Furthermore, AI tracks updates and automatically incorporates them across your sales channels, saving time and ensuring your information is always current. In addition, it continuously monitors product information from major marketplaces such as Amazon and Shopify for you so that you can provide the most accurate product data available.

You also combine your team’s valuable experience with AI’s abilities to help AI differentiate very similar attributes, further increasing accuracy.

As your term confirms accuracy, machine learning adds this to AI’s knowledge, with each improvement further reducing the time and effort required by your team. It’s very symbiotic.

3. Bulk validation

Validation is yet another time-consuming process, especially when onboarding products in bulk. Advanced AI modules automatically analyze product information, including uploaded images.

It can identify objects visually to determine what they are and then add relevant tags. Tags are added based on “confidence” levels based on either an 80% threshold or user-defined features. The confidence levels help you understand the reliability of product information, especially when sourced from an outside party in bulk.

In essence, AI can also identify and point out attributes of products tens of thousands at a time during the bulk onboarding process to ensure information is correct.

4. Image recognition and optimization

As mentioned, AI uses image recognition to streamline bulk validation. Pimberly uses image recognition to quickly identify and classify products, a valuable feature for brands with multiple product variations such as sizes, colors, and other customizable attributes.

AI image recognition also recognizes different product parts and can extract the appropriate function-related features. Again, applying tags based on an 80% threshold confidence level or user-defined attributes enables you to optimize product descriptions.

And, back to machine learning, image recognition AI also continuously adapts and improves its knowledge to improve meta-tag labeling and to create enriched product information that is search engine optimized. Product images are also adjusted for their respective channels so your team easily meets the needs of channel-specific formatting requirements.

AI product image recognition in Pimberly’s PIM/DAM manages both structured and unstructured data, enabling you to turn the unstructured data of images into structured data as product information. This is a huge benefit when onboarding products as it saves time and effort writing text and repurposing it to suit each channel.

As a result, you streamline cross-channel onboarding processes with proper attribute requirements for each marketplace.

In addition, you have an all-in-one automated description with text-based information related to the images, metadata, and attributes pulled from a single pipeline.

Customer experience

Product image recognition improves customer experience by offering similar product recommendations using attributes that help narrow down customer searches. For example, once new products are onboarded, they can be searched and recommended if a similar product is out of stock. Also, onboarded products can quickly be added for recommendations on complementary products to increase average basket value.

Pimberly AI is designed to improve your product onboarding process, leveraging machine learning and image recognition to streamline the process, improve accuracy, and speed up time-to-market. For more information, click here to set up a PIM demo.