What is Recommend?
RMC Recommend is a recommendation engine which analyses real-time user behaviour, purchase history and customer preferences and uses this to deliver personalised recommendations to all your customers across email, mobile, social and web.
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email Playbooks - Out of the box email execution
AgilOne also also comes with built in capabilities for triggered and hyper-targeted email campaigns. A predetermined number of emails per active customer are included in every subscription. Get started today with AgilOne’s s out of the box customer lifecycle campaigns and templates, which include dynamic content for each customer.
Why should I be using Recommend?
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- Browse abandonment campaigns – Send known visitors who browse without adding anything in their cart an email to bring them back to your site to incentivise them to make a purchase. Recommend products and categories based on each visitors individual browsing history, and show recently viewed items (product or category) to motivate additional purchases.
- Cart abandonment campaigns – Encourage would-be customers to complete their purchase when they leave items in their shopping cart. Automatically send known visitors an email that includes the items they selected onsite and also recommend related items based on their selection to inspire further shopping.
- Post-purchase campaigns – Post-purchase emails provide a strong cross-sell opportunity. Include product recommendations triggered by the customer's purchase history to increase customer lifetime value.
- Replenishment campaigns – Trigger personalised replenishment emails based on each individual customer's purchasing cycle, and remind customers to repurchase products just before they run out, automatically. Increase customer lifetime value and increase your customer retention rates.
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For more information about these campaigns and to view more out of the box lifecycle campaigns, see Email Playbooks.
Enhance the Customer Experience Across Your Entire Web and Mobile Sites
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- Product discovery– Recommend products in the same category the user is viewing.
Recommendation types: Viewed this / Viewed that, Viewed this / Bought that, Recommendations for you (based on purchase history), Recently viewed (based on browse history). - Complement purchasepurchase – Recommend products in different categories based on customer purchase history.
Recommendation types: Frequently bought together, Related items, Complete the look. - Inventory considerations– Recommendations products based on business rules as well as customer browsing and purchase history.
Recommendation types: Best Sellerssellers, Trending Nownow, New Arrivalsarrivals, New Markdownsmarkdowns, We Recommendrecommend.
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For more information about these campaigns and to view more out of the box lifecycle campaigns, see Web Playbooks.
How do we know Recommend works?
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