Dynamic Yield is presented as an AI-powered Experience Optimization platform that delivers individualized experiences at every customer touchpoint: web, apps, email, kiosks, IoT, and call centers. The platform’s data management capabilities provide for a unified view of the customer, to allow the rapid and scalable creation of highly targeted digital interactions. Marketers, product managers, and engineers use Dynamic Yield for: Launching new personalization…
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IBM Watson Discovery
Score 9.1 out of 10
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IBM offers Watson Discovery, a natural language processing (NLP) application with options to measure sentiment, detect entities, semantic roles, and other concepts.
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Dynamic Yield
IBM Watson Discovery
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Dynamic Yield
IBM Watson Discovery
Free Trial
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Yes
Free/Freemium Version
No
No
Premium Consulting/Integration Services
Yes
Yes
Entry-level Setup Fee
No setup fee
No setup fee
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Dynamic Yield
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For us, it is well suited for personalization. Since we are hospitality brand, we have different rooms sales inclusion based on different segmentation like Mem or Non-mem, Global or UAE, we have to personalize our landing pages accordingly so that we show the relevant information to relevant audience. The inactivity pop up box and newsletter signup popups work good for us. It does not work well in some scenario like Dynamic Yield offers built-in analytics focused on campaign and test performance, but it’s not a replacement for tools like GA4, Adobe Analytics. It lacks deep funnel tracking or complex reporting capabilities.
Overall, IBM Watson Discovery is an amazing technology that we use with our clients to address various business problems, but the biggest challenge has always been about ingesting, analyzing, enriching, and searching huge collections of documents and allowing our end users and SMEs to be able to search for what they need to reduce the time and efforts spent daily on a manual search through various collections of documents. We have successfully managed to reduce manual work by over 80%, and now our SMEs are being used for the skills they have to gather insights rather than do manual work.
Provide fantastic support, both in relation to strategy/best practice and troubleshooting.
An easy to use interface, as a user who is relatively new to Dynamic Yield I find that it is an intuitive platform to use.
The ability to segment and drill down on data allows for really specific insights which, whilst not necessarily being leveraged on a testing basis, can be super valuable from a greater marketing perspective.
Brand templates could need complex CSS/custom code.
We'd like to see a little "i" next to specific labels, which elaborates on what is meant. For example, when I hover over "Dynamic allocation," I get something like "An advanced form of A/B testing where the best-performing variations receive higher traffic."
Jargon (for example, for audience targeting) can be overwhelming for new users; therefore, clearer, user-friendly explanations are needed.
I believe AI should be more flexible about providing data. However, it's understandable that you need to provide the details you need in a more specific and detailed way.
The interface could use more tweaking. Being new to the program, it was kind of hard to navigate.
Luckily, there was a customized feature of the dashboard that I could set up, and having something that you know where you are placed always feels familiar and comfortable.
implementation took a long time but also, DY has really proven that they are transforming and adapting their platform to be more user friendly and the right technology choice for their brand or company
Setting up strategies, audiences, and experiences is simple and fast. It is incredibly easy to modify the appearance of your site and optimize every aspect with the Dynamic Yield Personalizations. However, while the data visualization on an experience level is easy to modify and analyze, exporting the data in meaningful ways is time consuming.
IBM Watson Discovery has the best user capabilities and easily transform business decision-making portfolio. The automation system saves time used in data analysis as opposed to manual research that consumes a lot of time. The visualization across the dashboard enables my team to interpret complex data and use it to make reliable marketing decisions.
Overall, the support is very good. If you are a partner (my case), they assign you a customer success manager, that helps a lot. Also, there is a technical person to provide support to the partners, again a great help.
My only "complain" is that with some complex issues, the support may delay in providing you with a solution. Sometimes that can cause some tension with your client.
Similar to all IBM Watson and Salesforce product solutions, the overall support would be a 10/10. Their provided FAQ's help with frequently experienced issues and if still unable to figure something out, their customer service representatives are always super responsive. With instant chat functions available, it is easy to ask a quick question rather than sitting on hold.
Dynamic Yield provides far more capability and ready-to-go templates for small-medium sized businesses, as well as decent API implementation for businesses who want to have a deeper integration. The ease of implementation and faster time-to-market is why we chose Dynamic Yield.
Discovery differs from its competitors due to the better ease of implementation and the high level of natural language recognition, it is equal in integration resources such as API and workflow or process pipeline, but it loses in the price for a high volume of documents and/or research. If you own or plan to use other services from the IBM Watson family, there is no doubt that Watson discovery is your best option. Another important point is if you plan to use a cloud or on-premise service (local server or private cloud).
Most tests have had a positive impact on either revenue or conversion rate - quite often in double digits.
Dynamic Yield has also helped us to stop some particular initiatives through direct interaction with the customer base via questionnaires or by a test proving negative quicker than rolling out a permanent feature.
