Gamooga

Solution for E-Commerce

Activation

‘First order discount’ displayed at the right moment can improve customer activation rate by 30%


Sara is an avid online shopper and loves purchasing trending apparels online. She sees an ad on her social media page and lands on an online retail shop. She browses through few dresses but decides to leave the website without purchasing anything. As soon as she reaches the close button she sees a banner offering 10% discount on registering with the e-tailer. She fills in her email ID and contact info and starts browsing again to take advantage of the discount.

Conversion

Improve conversion rate by 15% by effective cart abandonment campaigns


Sara adds few products to the cart but after a while leaves the website without checking out. After around 15 minutes of leaving the website, she receives a browser push notification reminding her of the products she abandoned in the cart along with an additional 5% discount if she completes the purchase in the next 10 minutes. She decides to avail the opportunity, clicks on the banner and completes her purchase with huge savings on the order.

Engagement

Email campaigns showing personalized recommendations can increase repeat customers by 12%


Since her last purchase, Sara hasn’t returned to the website. She receives an email showcasing all new styles launched on the website in the genre of dresses she purchased last time along with some personalized recommendations. She clicks on one of the styles she likes and lands back on the website and start scrolling through the new collection.

Retention

Personalized offers communicated through the right channel can improve customer retention by 25%


It’s been almost a month since Sara has visited the website and shopped anything. An email as well as an SMS containing an exclusive ‘MISS YOU’ voucher code has been sent to her that provides her 10% discount on her next three consecutive purchases. She clicks on the link to the landing page accompanied with the code and comes across all new styles. She is excited by the exclusive approach and starts browsing the website again to avail her special discount.

Hyper Personalized Website & Mobile Shopping Experience

Create personalized real-time cart abandonment campaigns

Retarget the customers who have put items in their carts but did not complete the checkout through emails, push notifications etc. in an automated and personalized manner.

Up-sell and cross-sell recommendations to relevant users

Behavioral targeting engine monitors browsing and purchase behavior of users. Based on this, customized product recommendations can be served to potential buyers on the website, email, push notifications etc.

360 degree view of a customer for cross-channel communication

Multi-channel activities of consumers like their online browsing history, personal data, purchase data, campaign response data etc. are available in a single view for marketers. This enables you to analyze and precisely target consumers with no need to manually merge data from different sources.

Detect optimum time & channel to communicate with different users

Identify each customer’s preferred time & channel to receive communication using statistical modeling techniques and machine learning algorithms. This enables marketers to optimize their email’s send time and drive higher open rates along with figuring out the best channel to communicate with each user.

Target about to churn customers with App Uninstall Prediction

Predict who is going to uninstall your app within the next 7 days and prevent them from Churning. The predictive analytics model calculates uninstall probability of every App user based on multiple prediction models through available data like last 30-day activities on the App, time spent, etc.

End-to-end analytics support for enhanced retention rate

Do end-to-end analysis of your campaign performance. Understand which marketing communication of yours is driving the customer back to your website/App, which channel is performing the best, what content is helping the user convert etc.