Algolia vs Dynamic Yield

• Algolia is brain-dead simple to set up. I've implemented search with Algolia in a dozen different ways now, and it never took me longer than a few minutes to get the functionality I want. With Algolia, the only challenge is designing your search UI -- if you don't want to use their baked in UI solutions.
• Results come back incredibly fast. I'm not sure how Algolia does it, but every keystroke I make in a search field returns new results instantly. It's hard to believe that I'm searching large datasets on a remote server when it works so fast.
• Very little customization is needed for 99% of use-cases. Algolia's out of the box setup works great, and it takes no prior knowledge to set up.

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• Product recommendations are easy to set up, and powerfully personalizable through either hands on refining or automated A/B testing
• Customer insights are easy to set up and can be applied retroactively to data
• A/B testing anything from different graphics to copy to page layouts is easy to set up and implement site wide

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• Algolia can be a bit complex -- for smaller companies or companies without many tech resources, it may be difficult to implement and use without the help of a third party
• Manually manipulating search results (for specific queries having listings show up first) is a bit difficult to do without custom developing that functionality

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• Their support team may delay when the issue has some complexity.
• Some integrations, like the triggered emails, can be more simple.
• Lack of a report to show the value of the tool. Right now, it requires some work to achieve this.
• I miss some CDP capabilities to create better segmentation.

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• It's too early to measure any increase in our transactions
• We have good customer feedback on the Algolia search function
• We are looking at other apps in development where we can also leverage the power of Algolia

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• 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.

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