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βetaout Q & A Product Deck Mayank Dhingra Co-Founder, Betaout

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Presentation on theme: "βetaout Q & A Product Deck Mayank Dhingra Co-Founder, Betaout"— Presentation transcript:

1 βetaout Q & A Product Deck Mayank Dhingra Co-Founder, Betaout
Ph: E: W: Skype: mayankdhingra Mayank Dhingra Co-Founder, Betaout

2 The Uncoordinated Marketing Dependency on I.T. Department
Problem with E-commerce Marketing The Uncoordinated Marketing Dependency on I.T. Department The Data Silos Today marketers use 5 or more marketing tools and have no single view of customer profile Customers are getting repeated, un-targeted messages across multiple channels creating a negative experience for them Data import & export, manual segmentation, customization and integration – marketers need constant help from tech teams

3 Omni-Channel Personalisation
What we do What we do 1 2 3 Real time Big-data Collect and Analyse user behaviour and intent across all devices Segmentation Real time customer segmentation based on business rules & machine learning Omni-Channel Personalisation Reach customers with personalised marketing via push, , sms, retargeting, in-app, in-web etc

4 Betaout – a plug and play, omni-channel marketing solution
IN-SITE Engagement WEB Loyal Customers Slipping Away REAL TIME NOTIFICATIONS MOBILE Personalization Engine MARKETING First time Customers Mobile Users Returning Visitors SOCIAL SOCIAL CRM or EXTERAL SOURCE MOBILE CREATE BEHAVIOURAL DATABASE WITH SEGMENTS MULTI-CHANNEL AUTOMATION BASED ON BEHAVIOR CAPTURE DATA FROM ALL CHANNELS

5 Some Use Cases Some of our Clients
Targeted Communication: Create segments and target users across multiple channels Lifecycle Management : Activate new, engage existing and reactivate lost users Cart Recovery: Set up multiple campaigns with sequence of s to recover abandoned carts Improving conversion via onsite engagement: Acquire new leads and improve conversion on product/other pages Up sell/Cross sell: Target users based on their purchase and behavioural data to give them relevant product recommendations


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