In an era where AI shapes every corner of our lives, the race to redefine customer engagement is on. As businesses dive deeper into the digital realm, the challenge isn’t just about collecting data but making real, meaningful connections with users.
MoEngage stands as a participant in this competitive sector, aiming to change the way brands understand and engage with their audiences through technology and insights.
Frontier Enterprise recently sat down with Raviteja Dodda, Co-founder & CEO of MoEngage, for a conversation. Dodda explores the shifting dynamics of AI-enhanced customer engagement, discussing strategies for achieving nuanced, effective user interactions.
You co-founded MoEngage with Yashwanth Kumar in 2014. What have been the highlights of your time there so far? What are the most significant technological milestones you’ve seen since then, specifically when it comes to customer engagement and analytics?
In 2014, alongside Yashwanth Kumar, I co-founded MoEngage with the vision of transforming omnichannel customer engagement and marketing automation. Our work has centred on enhancing how brands communicate with their customers, facilitating billions of messages and omnichannel experiences monthly.
Our technological journey has been characterised by:
- The adoption of insight-led engagement strategies to keep up with changing consumer behaviours and market demands.
- The integration of AI and machine learning to push the boundaries of personalised, customer-centric marketing.
- Emphasising the importance of digital transformation for business sustainability and competitive advantage.
- Advancing the capabilities of multi-channel and omnichannel campaign orchestration for cohesive customer experiences.
- Focusing on hyper-personalisation and contextual segmentation using zero/first-party data, which is a make-or-break requirement in today’s market.
With the impending demise of third-party cookies, what strategies is MoEngage using to ensure effective customer engagement while adhering to privacy norms? How is this shift affecting your platform’s approach to data collection and analysis?
At MoEngage, data security, collation, and analysis have always been top priorities. Recognising the importance of safeguarding our customers’ data has been an essential part of our ethos since our inception. We have actively adopted the latest globally recognised security policies and sought to strengthen our products to ensure the protection of customer data, particularly for enterprise brands that cater to millions of consumers globally.
Because we’re committed to data security, we have engaged with independent third-party security firms to evaluate our products and enhance our data privacy and security measures. We seek to adhere to compliance standards including GDPR, CCPA, SOC2 Type 2, CSA STAR Level 2, ISO 27001:2013, and HIPAA, and offer secure authentication and single sign-on options for added data protection.
Furthermore, we were recently able to achieve the ISO 27001:2022 certification. This reflects our ongoing efforts to implement robust security measures and adhere to the highest standards of compliance.
In addressing the shift away from third-party cookies, we have introduced PII tokenisation. This approach lets consumer brands engage and drive meaningful campaigns without storing sensitive customer information.
What are the biggest challenges you foresee for companies integrating AI into their customer engagement strategies? How should they navigate these challenges?
AI-powered automation is set to enhance operational efficiency for businesses, with a shift towards personalised engagement strategies to improve customer satisfaction and loyalty. As these technologies advance, trust and ethical considerations will be paramount.
Companies will need to establish clear guidelines, ensure unbiased use of customer data, and conduct rigorous testing to eliminate biases in predictive algorithms. These steps are essential for building trust and mitigating risks associated with AI implementation.
How is generative AI being integrated into MoEngage’s own internal processes? What improvements or new capabilities has this integration brought about?
Our go-to-market and customer success teams have integrated generative AI-powered platforms. These platforms are used to enhance our processes for responding to vendor assessments, requests for proposals, and tenders.
Additionally, we use generative AI to develop support assistants. These assistants are designed to offer quick and efficient solutions by leveraging our existing knowledge base and insights from past query resolutions.
These integrations have helped drive better closures, enhancing our sales pipeline value, and quicker resolutions, leading to higher customer satisfaction.
What are MoEngage’s top technology challenges in this age of AI? What are its technology goals for 2024?
Our goals include resolving anonymous or duplicate user profiles through identity resolution and user management. We plan to enhance data transparency, quality, and reliability. Our team also plans to sync segments from data warehouses to MoEngage more seamlessly with warehouse audiences. Furthermore, we will focus on increasing personalisation and experimentation with server-side APIs, AI-powered testing, diverse templates, and updates.
Improved deliverability tracking, analytics, and reachability will be our other areas of focus. We also aim to help brands gain a better understanding of the ROI of campaigns through our analytics dashboard, and will help in mapping customers across multiple applications with a multi-app unified customer view.
Our vision involves transforming into a multi-product suite for customer experience management. We aim to offer real-time, personalised, and connected experiences based on actionable insights.
What are some of the most exciting developments in MoEngage’s labs?
MoEngage’s labs are developing several key features that aim to enhance our platform’s capabilities:
- Enhanced insights through a new analytics module, which includes new dashboards and supports advanced data types.
- Enhanced omnichannel communication through the addition of bidirectional conversation and MMS support, expanded functionalities for WhatsApp, email, and push notifications.
- Advanced personalisation achieved through new recommendation engines, APIs, and a variety of templates.
- Utilisation of generative AI for the production of visuals and content, aiming to enhance campaign effectiveness.
- Expanded integration capabilities with data warehouses, CRM systems, advertising platforms, and social media networks.
- Transactional Messaging improvements with the introduction of new channels, enhanced personalisation features, and increased security measures.
