Comparing recommendation tools: Marketing Cloud Salesforce vs Google Recommendation AI vs AWS Personalize
Some of you may think it’s so bizarre to try to compare Marketing Cloud Salesforce’s Recommendation engine, AWS recommendation engine, and Google’s Recommendation AI as they are so so so different. But when you are trying to find a proper solution (as I did) for your personalization program, you have to jump through multiple hoops and consider many options.
As I mentioned in my early article about personalization tools, a recommendation engine would come with some core components as:
- Catalog — a micro-database of the content which could be a product catalog or content or elements of interaction
- Real-time behavioral data feed
- The “brain” — the algorithm
In addition to the core components, when choosing your ideal solution, you may consider other factors as:
- a build-in UI to deploy the experience,
- opportunity to customize the “brain”
- upload the historical customer engagement data.
- upload offline customer data.
Those details could have seemed unimportant but I consider them a deal-breaker. Let’s review the AWS Personalize, Google Recommendation AI and Salesforce Marketing Cloud Web/email recommendation engines.
Comparing CORE COMPONENTS
DEAL-BREAKERS
On my personal taste, Marketing Cloud provides the most convenient tool to develop and deploy the web and email recommendation program. Also, it works very well for known and unknown visitors to your site. With some patience, AWS could be very helpful to provide personalized experience for your existing customers. Very helpful tool if you have an extensive customer base and you want to make their life even better. Google’s algorithm would be the most efficient to drive reveniew for e-commerce business whose customers are mostly unknown.
As usual, thanks for your visit and if you have something to discuss or have an exciting personalization project to build, reach me out:
LI: https://www.linkedin.com/in/marinazub/
Twitter: @MarinaZubTech
IG: Marina.Zub
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