Media Announcement: Adaptive Machine learning has been in use in its crude forms for many years now. The spell-checkers are a classic example of this technology. In recent times, adaptive machine learning has grown in demand among the marketing fraternity with increasing spend over digital platforms. Also, the availability of vast amounts of data pertaining to a prospect or a customer is now more readily available. This big data when churned through a machine learning algorithm creates meaningful and proactive marketing decisions and communications pertinent to the customer’s wants.
Retainly’s Marketing Automation Platform has been purpose built for Bloggers, SaaS products, Digital Media Companies, Real Estate, Internet Business, and eCommerce. It has ready integration to pull customer related data from multiple sources including Woopra, Mixpanel, WordPress, and Intercom. So if a marketer is already using any of these analytics platforms, then a single click can sync all their customer data and events into Retainly. The integration is real-time which ensures that the user need not keep revisiting. Integrations with Segment and Heap Analytics are on the way in the subsequent release. Retainly also has it’s own analytical tracking script which saves the trouble of uploading subscribers, leads or new signups on a daily basis.
Retainly offers multiple channels of communication not restricting marketers to email alone. Businesses where customers are more active on mobile phones, marketing campaigns can be sent via SMS. This channel suits the Real Estate companies more. For bloggers and digital media companies, use of the email channel is more prevalent. For SaaS product companies, In-app notifications, as well as email marketing is a definite winner. Push notifications are coming in the next release which will help eCommerce companies a lot.
While Retainly has features for traditional marketing agencies to bulk upload their subscriber’s information and send blast campaigns and newsletters, the actual adaptive learning starts with the advanced Behavioural Marketing module. The system configuration done once can detect events and send automatic real-time and relevant notifications to customers based on their actions and activity. The Adaptive Machine Learning has been used to create dynamic live customer segments where customers can automatically move from one segment to another based on the properties defined. Although Machine Learning is a complex science, Retainly has simplified it to the surprise of the end user. As a marketer one will never encounter any complexity in configuring the system to adapt to unique business needs. Flexibility has been the key focus area to accommodate every possible marketing scenario. Off course Retainly also has the time-delayed and sequence Drip Marketing campaign which is extremely popular with SaaS companies and organizations offering training over emails.
Aside, Retainly has the world’s only email checker tool to test emails for spammy content. Retainly has opened up this innovative testing platform for free unlimited usage by the email marketing community. A unique blogger search platform has also been offered free to help bloggers get more quality traffic and visibility.
The adaptive machine learning will continue to build more applications in Retainly’s subsequent releases. This article elaborates on how Retainly is using the Adaptive Learning for their Marketing Automation Platform. The platform benefits companies and people to embrace better email marketing practices by sending near accurate, very relevant, and very on-time communications to their customers. Retainly helps reduce the Inbox clutters from non-relevant promotions and assists in a better conversion of Leads and improved retention of customers.
Retainly is a Startup enabling Multi-Channel Drip Marketing Automation with Email, SMS, In-App & Push Notifications. It helps SaaS companies, Bloggers & Digital Media, e-commerce companies, tutorials, reality and others to engage customers with time-delayed and behavioural automation.