There is no denying the impact AI is having in the customer journey. A recent HubSpot survey highlights how critical AI is to CX leaders where 84% of respondents say AI/automation tools will be instrumental in helping them meet customer service expectations.
In addition, 86% say AI will transform the experience customers get with their company, and 75% also agree that AI/automation tools will help improve customer service response time.
Generative AI has led to increasing interest in how AI should be used in the customer journey, and we have reached another major breakthrough in how AI tools can process and understand information: multimodal AI.
What is multimodal AI?
Multimodal AI refers to artificial intelligence systems that can process and integrate multiple types of data or "modalities" simultaneously, such as text, images, audio, and video. This allows the AI to understand and generate responses based on a combination of these different forms of information, making it more versatile and capable of tasks that require cross-modal understanding.
What benefits does multimodal AI have?
Better voice interactions
Legacy AI systems processed voice inputs by first transcribing them to text. This introduced a few challenges: accuracy and latency.
Even the best transcription systems fall short of 100% accuracy meaning that any AI solution that relies on transcription to process voice inputs is inherently inaccurate.
Additionally, delays are introduced by transcribing voice to text, processing the text and re-rendering it as voice output. This creates an unnatural cadence to AI voice conversations. Multimodal AI models fix these issues by not relying on transcription those increasing their accuracy and minimizing latency creating more accurate and human like interactions.
Enhanced understanding of customer emotions
By now you have likely heard of sentiment analysis. This technique assigns a "score" to an interaction broadly defining it as positive, negative or neutral. By processing voice interactions natively, in multimodal AI models, speech emotion recognition (SER) can analyze aspects of speech like pitch, tone, loudness, speed, and pauses.
These features vary with emotional states (e.g., a higher pitch might indicate excitement or anger, while a slower, softer voice might suggest sadness).
Models trained on voice samples help the AI distinguish emotions like anger, happiness, sadness, fear, and neutrality from the way people speak.
Deeper and richer understanding of customer needs
By processing all interactions, a customer has, no matter the medium (voice, chat, etc.) we can holistically understand the entirety of a customer's journey as well as the emotions they were experiencing throughout the process. By bringing together all modalities of interaction under one model we can seek to understand our customer in a more comprehensive way, as well as provide, a more seamless omnichannel experience.
Increased personalization
Multimodal AI systems can take recommendations to another level.
Troubleshooting an issue over the phone?
Imagine being able to upload a picture or video to technical support and receiving back specific troubleshooting steps that go far behind simplistic one size fits all troubleshooting checklists. No more being asked repetitive or irrelevant questions to fix your problem.
How about finding that perfect outfit for a special occasion. Upload a picture of something you like but isn't quite right and get highly targeted results returned back that closely mirror what you already like but offer other options that may end up being your perfect fit.
More accessible customer service
Too often are best customer experience tools are locked behind a modality (text, speech, etc.). By being able to train AI models that can react to any method of input you can finally cater to diverse customer needs by providing accessible options for interaction. For example, visually impaired users can interact through voice commands, while hearing-impaired users can rely on text and visual cues, ensuring that everyone has equal access to support and services.
In short, multimodal AI models will create more human like interactions that feel much more responsive and intuitive to your customer's needs. Ready to explore how AI can create a better customer experience for your company? Contact us here.