Harnessesing the Power of Messaging for Brands
Msg.ai’s artificial intelligence platform helps brands take advantage of the surge in consumer messaging by building conversational interfaces that enable personalized interaction with the brand throughout a customer’s journey. They’ve helped numerous brands across industries create a wide variety of highly personalized bots to delight consumers and create valuable engagement and drive commerce.
We caught up with the folks at msg.ai recently to learn more.
In 100 words or less describe what your company does.
Msg.ai empowers brands to build conversational interfaces and bots that engage in highly personalized, 1-on-1 and group conversations across the customer journey. Our deep neural networks marry consumer intent with historical customer context and real-time situational models to enable bots and bot + agent combinations to delight customers.
Our brand partners’ highly intelligent conversational bots are creating frictionless, highly interactive and on-demand consumer experiences on Messenger, whether it’s providing a personalized VIP personal stylist, or a skin care expert who recommends a tailored beauty regimen based on a user’s skin type and goals, or closed loop commerce and customer care, among many other use cases, msg.ai integrates with a brands’ existing CRM, ecommerce, support and other systems and uses deep reinforcement learning.
Who are you trying to reach?
We partner with the world’s biggest brands across a huge mix of industries, all seeking to transform their customer experience through messaging. Our partners leverage Messenger in a unique way to reach consumers. Whether it’s enabling fashion-forward brand loyalists to shop a new collection as models are walking down a Fashion Week runway, customizing their own version of a new high-end car, or eliminating pain points from current customer support channels.
How did you go about designing your platform?
Our platform is built on the combination of three key concepts: user intent, customer context and history, and situational awareness. We identify what a consumer is looking for in-the-moment, and deliver the right content and experience in real-time, learning to address the user’s intent and situation with the best possible action from the brand. We also apply multivariate testing on real-time data including responses, rich media, bot tone, etc. to discover what resonates with consumers. The bot then learns on an ongoing basis and becomes significantly smarter with more interactions.
What have you learned since launching?
We’ve learned a few key aspects since launching the first brand bot on Messenger in 2015:
- Situational Context: It’s incredibly important to tap into as many situational factors to drive immediate relevance to the consumer. For instance, offering a different experience if someone is in aisle versus at home.
- Memory: Creating experiences that build off previous conversations is essential. Not making a person re-tell you things about themselves on return visits helps alleviate consumer frustration while getting deeper into personalized experiences faster.
- Pictures, Pictures and More Pictures: Consumers are not satisfied just communicating in text and tap. There is a desire to share pictures to tell the AI bot about themselves, their current needs and their situation.
On an individual bot level, we’re applying A/B testing to learn what tone and personality resonate with consumers. What is dreamed up in a brand marketing brainstorming session, isn’t always what captures consumers’ attention.
Any surprises or successes you want to share?
The use cases for successful AI bots that consumers engage, and reengage with, vary extraordinarily.
With Tommy Hilfiger, we invited consumers to shop the new collection from Fashion Week immediately via Messenger (a first in the fashion industry), a bot that experiences an 87% return rate. On the other hand, Signal, a Unilever oral care brand, is helping children establish good brushing habits via a series of interactive episodes and challenges over a 21-day period.
What will you build next?
In addition to being able to have text and tap conversations, we’re working to enable our bots to “see” through visual recognition and let the user interact with Facebook’s new AR [DG3] toolkit. The way we communicate is increasingly visual through images and videos. We empower consumers to share images with a bot to trigger a rich experience, whether it’s styling based on a person’s look or clothes, recommending a hairstyle based on someone’s face shape, or troubleshooting.
As bots mature beyond first-generation experiences, we’re building the platform for brands to have a multi-bot ecosystem. We envision a brand having multiple bots that are deep experts in different micro-content areas, as well as external events (such as major changes in pop culture, news, etc). During a single exchange with a user, a bot could connect to one another within the same conversation: passing along the conversation seamlessly to another bot or calling a bot in the back-end for information in real-time.
With over 1.2B active users, it’s where our brand partners want to be as it is the platform that their customers are on and use every day. It’s truly universal.
The Messenger team is dedicated to creating a major shift in today’s customer experience. Whether it’s through developer tools that create an interactive user experience, or constant innovation in driving discoverability, their vision for the role AI bots can play in the consumer and brand relationship has driven an entire global shift.
Our Building Bots for Messenger series highlights different experiences on the Messenger platform. These businesses and developers have approached building their bots in a unique and interesting way, and are seeing success on the Messenger platform. Look for more bot profiles right here on the Messenger blog.