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How to Leverage AI for Customer Communications
In the past, AI was largely leveraged in situations requiring repetition and precision. However, the advent of large language models (LLM) and Generative AI - like ChatGPT and Bard – has birthed a new genre of humanified AI. Today, AI finds a place in customer communication owing to its deeper and more contextual understanding of human language and behavior.
AI tools can add scalability and efficiency to customer communications while maintaining a human touch. They can generate net new responses for every customer query, scenario and prompt, which sounds organic and un-robotic.
What else?
For global businesses, AI tools can communicate in multiple languages, articulating customer communication in a way that creates instant affinity with local audiences. Moreover, they can be engineered to be devoid of human error, bias and prejudice in their output.
All in all, AI is no longer confined to the business backend. It is the face of modern businesses and plays an active role in all business functions, including customer communications.
Practical applications of AI in customer communications
Early adopters of AI can grow their use cases and business benefits as the technology matures and pervades new tasks and operations. They can unlock the transformative impact of AI and stride ahead of the competition by leaps and bounds.
Sounds interesting, right?
Consider these practical applications and examples of AI in customer/client communications and use them to shape and strengthen your communication strategy.
1. Customer Support
AI in customer service is nothing new. From conversational chatbots to voice bots, from predictive CSAT to sentiment analysis, AI has helped automate, scale and optimize customer support for brands. In the context of support-related customer communications, AI is playing a vital role in:
- Providing 24/7 responses via customer self-serve tools like chatbots and voice bots. These tools are available round the clock, enabling customers to communicate with brands on demand. They can handle multiple conversations concurrently, providing quick responses to routine, repetitive questions to improve customer engagement and customer satisfaction (CSAT) with brands.
- Consistent, on-brand communication across all channels and customer touchpoints. Omnichannel bots can respond to users in channel-native language that also complies with brand guidelines. Exposure to harmonious messaging fosters customer trust and builds brand recall, which can help cut through the noise and grab more eyeballs.How consistent brand experiences are createdWATCH THE VIDEO
- Accurate sentiment and intent detection enable customer support teams to control conversations agilely, manage emotions and avoid escalations. Sophisticated AI tools don’t get thrown off when users switch their intent and are able to handle out-of-context queries intelligently.
- AI-led routing to match cases to agents who possess the requisite skills, bandwidth and experience for efficient resolution. AI enables supervisors to calibrate the team’s proficiency level objectively, so they are assigned cases they are best equipped to handle.
Inspiring example: Sephora
French cosmetic giant, Sephora, delights website users with their pathbreaking chatbot – KiK. Complementing their in-store experience, KiK allows users to match foundation to skin shades, book appointments and try on different make-up looks. Needless to say, KiK’s AI is responsible for the great online support experience that engages make-up lovers and brings them back to Sephora over and over.
Need more examples? Read 15 more inspiring chatbot success stories
2. Marketing
AI can fine-tune marketing communications and improve your share of voice in a crowded marketplace. This happens in three major ways:
- Predictive analysis and customer insights: AI tools are capable of crunching vast datasets to uncover trends in customer behaviors, needs and preferences. It can reveal your audience’s preferred channels and moments of need, allowing marketers to do customer profiling, audience targeting and content creation with agility and efficiency.
- Automated email marketing: If email outreach is a mainstay of your marketing strategy, AI can be a trusty sidekick with accurate customer segmentation and content personalization. It even recommends content plugs for each customer segment. When the right messages reach the right customer at the right time, corporate communication becomes a game-changer for any business.
- Varied customer engagement models: Marketing communications revolves around relationship building. That’s where AI can help build tailored customer engagement models for different audience groups.
For example, a high-touch model is key for brands selling complex, high-value offerings to a small focus group of clients. Conversely, a low-touch model is great for companies that aspire to scale their reach rapidly. And retention-type models are instrumental for subscription-based verticals like SaaS.
Inspiring Example: Vodafone
When Vodafone Germany wanted to expand their ROAS (return on advertising spend) from social media, they used Sprinklr Advertising, which boosted organic posts in key categories.
Using AI, the tool identified categories and created several ad campaigns on different social platforms. The initiative yielded big savings for the company that manages all its social media advertising with just three personnel, with Sprinklr doing most of the heavy lifting in terms of content creation and analytics.
3. Sales
Sales is the lifeblood of business and is becoming increasingly challenging with cut-throat competition and heightened buyer expectations. That’s where AI enters the picture and plays a game-changing role in sales communications. Let’s discuss this in detail.
- AI-led lead scoring: AI can analyze and prioritize leads based on their historical behavior and contact intensity. Armed with these insights, sales reps know where to focus their efforts to get the quickest ROI. This kind of strategic communication is more results-oriented and effective than the traditional approach of random cold calling or purchased caller lists.
Learn more: Lead Scoring by Contact Intensity - What Does it Mean? - Personalized sales outreach: As discussed, modern customers yearn for personal connections, even from brands they prefer. AI enables dynamic content creation - from emails to offers – that is tailored to each customer profile. Especially on cluttered social media platforms, personalized content stands out and catches the eye.
Research proves social sellers are 51% more likely to reach their sales quota with personalized content. That’s where AI-powered solutions like Sprinklr’s Sales Engagement platform can help produce customized posts with tones and captions that appeal to specific audience segments.
Dive deeper: A Detailed Guide on Social Selling - Upselling with tailored messaging. Customer acquisition costs are shooting through the roof, which means brands need to double down on reconverting their existing customers by upselling and cross-selling. AI can help surface relevant product recommendations and messaging to encourage one-time customers to buy again.
With proactive social listening, AI tools are able to detect what customers are looking for and recommend the right products to them. Since customers would rather buy from brands they have previously engaged with, upselling to them is easier than to random prospects.
Inspiring Example: Latin American Telecom Provider
A prominent Latin American Telecom Service provider aspired to convert pre-paid customers to post-paid by creating a seamless buying experience on the popular messaging platform – WhatsApp. They used Sprinklr Social’s Journey Facilitator function to build customized customer journeys on the platform and upsell their services to existing customers painlessly.
The result?
Their upselling campaigns on WhatsApp witnessed an astounding 80% open rate, leading to 110K upsells just from that channel. Today, 20% of their sales are attributed to digital channels, of which WhatsApp is a major player.
5 Pitfalls with AI-led customer communications [+ Solutions]
While using AI in customer communications brings a lot to the table in terms of efficiency, scalability and personalization, it’s not free of risks and challenges. Here are the top five you should avoid:
- Overreliance on AI automation: Beware of over-automating your customer responses and try to preserve a human touch, especially in scenarios that demand customer empathy and higher-order thinking skills. Even advanced technologies like generative AI in customer service should be implemented under agent supervision.
- Faulty data security: Oftentimes, AI-powered customer communications end up compromising data privacy in a bid to personalize messaging. This can lead to a breach of customer trust and legal conflicts in the worst cases. Ensure you use AI tools that offer enterprise-grade security and comply with industry regulations to stay on the right side of the law.
Learn more: A-Z of Contact Center Compliance [A Comprehensive Checklist for Brands] - Biased algorithms: Lop-sided training data can produce skewed results from AI tools. For instance, if a target group is over-represented in your training data, the algorithm may base all the results on this group’s variables, ignoring the other groups altogether, which can be counter-productive in customer communication. Regularly audit and clean up your training data or use self-learning AI solutions that iterate algorithms at fixed time intervals.
- Lack of transparency: Opaque AI systems keep customers in the dark and breed distrust and disengagement. Ensure your interface communicates when AI is being used and how your customers can practice discretion while imparting personally identifiable information. This way, you can prevent “AI hallucinations,” especially with infantile technologies like generative AI.
Read about Responsible AI in 2023 and Beyond - Neglection of customer feedback: Customers are your best auditors and advocates. Ignoring their feedback leads to missed improvement opportunities. Ensure your AI tools solicit feedback and continuous learning to risk-proof customer communications.
Find customer surveys too intrusive? Here are other ways to gather customer feedback.
Disruptive AI technology shows no signs of abating. To yield its power responsibly, you need to invest in a technology solution that is purpose-built for governance, compliance and data security. That’s where Sprinklr AI, with demonstrated AI success, merges as a frontrunner and a trusted technology partner for 9 out of 10 global enterprises, including Prada and Asahi.
Embrace disruption with Sprinklr AI
Scale, automate and risk-proof your customer communication strategy today.
Cliched it may sound, but it’s true: with great power comes great responsibility.
Sprinklr AI leverages the power and potential of AI, giving real business gains along with data security and risk mitigation, with features such as:
- Smart response compliance to screen each message for profanity, relevance and tonality.
- Channel-specific content with automated approval workflows to ensure on-brand and on-channel content.
- Campaign idea generation with hashtags, posts, themes and briefs with minimal manual intervention to help scale and automate content production.
- Granular insights to help capture sentiment across unstructured conversations and create listening queries on the fly.
- Generative AI integration to engineer personalized prompts and responses in conjunction with prevalent tools like ChatGPT and Bard.
With Sprinklr AI enriching customer communications with real-time insights and brand guidelines, you can delight your customers with on-target content that wins trust and deepens the relationship. Take Sprinklr for a free trial and witness the results first-hand.
Frequently Asked Questions
AI technologies that play a key role in customer communications include:
- Natural language processing or NLP
- Predictive analysis
- Chatbots and virtual assistants
- Personalization engines
- Speech recognition
While using AI in customer communications ensures transparency about AI usage, prevents bias in algorithms, and safeguards customer privacy by encrypting and masking sensitive data. Additionally, there is a fine balance between automation and human touch to prevent robotic, unnatural interactions.
AI-powered communication can be made accessible to customers with special needs by thoughtful design and ensuring compatibility with screen readers and other prevalent technologies. Such customers should be allowed to use alternative communication channels like voice-activated commands. All of this ensures that communication caters to customers with diverse and special needs.