Competitive markets demand competitive pricing

Are you having gross and net margin pressures in your industry? Having a hard time keeping pace with the competition? Take a look at this great interview Natalie Lamb, Vice President, Europe – Watson Customer Engagement, has with Paul Rodford, Finance Director at the Southern Cooperative, and learn how Paul and his team uses IBM’s Price Optimization offering to help them compete in a very competitive market.

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Teaching Watson Baseball Cards Part 2 – Team recognition

In this video I extend my visual recognition models to include more samples and now two teams. Let’s see how the results are with over 100 samples in each class identifier.

Video: Build a bot in 6 minutes with IBM Watson Conversation

Really good video and tutorial from Chris^2 about building a Watson Chatbot. Great job guys!

Taking advantage of user generated content with Stackla and Watson Content Hub

In this episode of Partner Connect I introduce Stackla – a content discovery engine focused on user generated content. I also share a prototype video created by my colleague Rob Enright who does a fantastic job showing how easy it is to use Stackla and integrate it with Watson Content Hub.

IBM’s Watson: Observe, Interpret, Evaluate, and Decide

IBM-Watson_logoWatson is a mystery to many and the casual observer thinks of Watson as a contestant on the popular TV game show Jeopardy where the super computer destroyed the human competition. This is one example application of Watson and what it is capable of.

 

Recently, Watson has been used in many industries to help humans make faster and even better decisions – like in marketing, supply chain, and health. A really good article I recently came across does an excellent job explaining in layman’s terms how this amazing technology works.

An IBM study found that 80 percent of the data out there — texts, tweets, blogs, articles, videos and even recorded sounds — cannot be understood by traditional programmatic computing. Watson is different: It translates this information into a form that is legible to its systems, and can therefore provide analytics based on these data points. – link

In case you haven’t seen Watson on Jeopardy, you can take some time to watch this video to see it in action. Just like Watson in for other industries, it was “taught” how to answer these questions. Processing the Jeopardy answer as described in the above article: Observing, Interpreting, Evaluating, and ultimately, Deciding.

Here are a few more areas where IBM is using Watson to help out different industries:

IBM® Watson™ Marketing Insights evaluates customer behavior by analyzing customer data that marketers provide. The results enable Watson Marketing Insights to predict likely changes in brand engagement, risk of leaving, and customer value. – link

IBM® Watson Commerce Insights empowers online and retail merchandisers, category managers, and marketers to manage their omni-channel business and customer engagement, both in-store and online. It is compatible with commerce, order management, and digital analytics platforms, giving broader visibility to business performance. – link

IBM Supply Chain Insights leverages Watson cognitive technology trained in supply chain to provide comprehensive visibility and insights across the entire supply chain. – link

IBM Watson Order Optimizer helps Omni-channel fulfillment practitioners in Retail leverage cognitive science to better understand their customers and drive real-time action. Through insight and analytics, they can make decisions, take actions, and build experiences that meet customer expectations and drive profitable business across digital and physical store channels. – link

Many of these offerings are represented in two video demonstrations my team put together to show how these solutions can help a B2C and B2B company operate with amazing efficiency. These are end to end demonstrations that show the breadth and depth of the Watson Customer Engagement platform.

a Watson Customer Engagement Story: Omni-channel

In this video I show how Evan and the marketing team use the Watson Customer Engagement portfolio to successfully execute an omni-channel campaign.

We start with Evan working with his team to set up an SEO strategy, dynamic pricing to compete against Amazon, and create a dashboard to monitor the customer experience and the performance of the site in comparison with the other categories. Watch how Evan and his team quickly setup and execute this campaign and also see what the customer Katie experiences across the web channel, call center, her mobile application and then lastly the store assistant.

FIT, Tommy Hilfiger, and IBM collaborate with AI

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Design by: Grace McCarty

Artificial intelligence is transforming all industries and the recent partnership of the Fashion Institute of Technology (FIT), Tommy Hilfiger, and IBM is a prime example of the possibilities. I am at NRF 2018 and IBM is showcasing this partnership at their booth #1922.

The design incorporates a special thread embedded in a futuristic, removable plaid panel with IBM’s Watson’s Tone Analyzer. It can then respond in near real-time to the sentiment in a customer’s social media accounts. Read more about the process and what Grace did to create this remarkable jacket. This is a really good example where artificial intelligence augments designers in the creativity process.

Taking our innovative spirit further, we partnered with IBM and the Fashion Institute of Technology on the Reimagine Retail project to explore how artificial intelligence (AI) can identify upcoming trends faster than industry insiders to enhance the design process. The goal was to equip the next generation of retail leaders with new skills, and bring informed inspiration to their designs with the help of AI. – link

To learn more about what Tommy Hilfiger did you can visit booth #1922 if you are at NRF or you can read this article that goes into detail the process Grace and FIT took in creating this jarket or you can read this blog post by Avery Baker, CBO, Tommy Hilfigerfor, a shorter version.

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