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The Future of AI for Team Productivity

The Future of AI for Team Productivity

The cloud of ChatGPT and a blip of Bard by Google is still hovering over content creators’ heads.

However, more artificial intelligence (AI) advancements are happening in other industries that are not on users’ radars yet. An instance that we will dive into today is conversational AI.

This virtual AI assistant technology is set to revolutionize the productivity of sales and customer service teams. From outdated cold calling and semi-auto support ticketing, using AI for Team Productivity can help streamline these processes.

What is AI?

AI means artificial intelligence.

According to IBM, artificial intelligence is;

” It is the science and engineering of making intelligent machines, especially intelligent computer programs. It relates to the task of using computers to understand human intelligence, but AI does not have to confine itself to biologically observable methods.”

In simple terms, artificial intelligence is machines’ simulation of human intelligence. The goal is to delegate repetitive tasks and complex human undertakings to machines for fast resolutions and accuracy.

How does artificial intelligence work?

Here is the technical part of AI.

Artificial intelligence combines large datasets, analyzing them and allowing the complex algorithm to learn, iterate and improve from the massive data fed in.

In simple terms, AI mimics human behaviors, thinking humanly and acting rationally.

Why Utilize AI for Team Productivity?

PwC predicts AI will likely add $16 trillion to the global economy by 2030, while Mckinsey predicts an additional $13 trillion in the same timeline.

Whether artificial intelligence will boost productivity, 81% of employees would increase their overall productivity. Here are some ways AI will boost overall productivity across different industries:

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  • Saving time spent on mundane tasks

AI for Team Productivity powers businesses to automate repetitive tasks. This increases employee productivity as they can focus on tasks that really matter.

For instance, sales reps can automate lead qualification and focus on building meaningful customer relationships for higher retention rates.

  • Increased staff engagement

Instead of having employees buried in their tasks all day, businesses can use AI to analyze and prioritize tasks. This enables employees to focus on the most relevant engagement that builds the business.

For instance, a business can use AI automation tools for team productivity to gather personalized feedback from employees. Then the company uses these insights to solve any issues among the staff as soon as they arise.

AI for Sales teams

We already have sales-enablement technologies in use for almost a decade now. However, sales AI tools take this sector to another level. According to research by Salesforce, high-performance teams are 4.9 times more likely to use AI tools than their counterparts that don’t.

AI is a great combination for small and medium-sized businesses (SMBs) focused on scaling revenues through sales. With sales AI tools, you have the capability to process data across sales channels and touchpoints into insights that fast-track deal closing.

Using AI Tools in Sales

Although only 37% of sales organizations are currently using AI, this number is steadily increasing. For sales teams, AI tools can help in the following functions:

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  • Accessing to real-time data for validity and accuracy
  • AI to personalize sales funnel experience for higher conversion rates.
  • Adapting buyer’s needs on the go – to improve customer experience
  • AI to gather and track all your prospects from sales opening to closing across multiple channels.

Here are some sales AI tools for improving team productivity and performance:

  1. AI for Lead Generation

Artificial intelligence lead generation tools turbocharge sales funnels. This enables sales teams to shorten the sales cycles while closing high-quality deals. SDRs can weave AI into the sales cycle in these ways:

  • For lead capture, use AI in your conversion rate optimization processes. The lead-capturing touch point can be a website or ad-capturing landing page.
  • For leads magnet, optimize them using AI tools to deliver personalized value that pushes visitors over the edge to take action.
  • For lead qualification, implement AI analytics tools to qualify and remove unwanted leads. The process fast-tracks
  • For lead segmentation, AI streamlines leads into categories and levels for better personalization and deal closing.
  1. Conversational AI

Conversational artificial intelligence for sales uses natural language processing (NLP) to analyze customer input in voice or text format. This AI solution helps customers to interact with customers humanly.

Examples of conversational AI for sales include:

Chatbots Aloha Bot is an example conversational AI solution for sales and support teams. We offer several features to power teams’ productivity and help them hit their sales targets.

  • In-app notifications
  • Appointment scheduling
  • Live chat system
  • Customized content-sharing feature

Voice assistants – Alexa and Siri hardware devices can bring sales leads directly into your sales funnel. For instance, Google Assistants enable users to optimize for voice keywords to generate leads to service and product owners.

Other tasks conversational AI solutions like Aloha Bot does include:

  • Onboarding new customers
  • Performance lead scoring based on customer interactions
  • Responding to frequently asked questions (FAQs)
  • Tracking updates like shipments for physical products
  • Nurturing leads through down-sell, discounts, and upsells opportunities

AI for Support teams

AI is vital in enabling real-time customer service.

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The following are ways artificial intelligence is empowering customer service support teams to deliver customer success;

  1. Enable self-service support – Using multi-channel touchpoints, AI enables support teams to offer service around the clock. They can reach customers and resolve issues via email, chatbot, social, or even phone.
  2. Pro-active complaint resolution – Using AI-data-driven and predictive analytics, support customers can solve complaints proactively. For instance, analyzing customer sentiment across channels is taking action before complaints get out of hand.

Practical AI use cases for customer service

  1. Multilingual support

You can detect the user’s preferred language using conversational AI solutions. Additionally, businesses have gone international with other solutions like omnichannel cloud contact center solutions; multilingual support can help retain and delight customers.

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2. Categorize support tickets

Using automatic tagging tools, SMBs can easily segment customer support tickets. With artificial intelligence, you can categorize customers’ support issues and assign relevant agents to solve them.

AI for Customer Success teams

Artificial intelligence customer success has evolved beyond offering insights and tangible execution tips. AI for customer success teams now has complex capabilities that offer predictive insights on customer engagement.

Customer success AI is set to provide SMBs and businesses with infrastructure that connects the dots between customers’ data and engagement to improve the customer’s life cycle. Some areas the AI will focus on include:

  • Customer led-AI product roadmaps – Instead of businesses launching new products or features from trends only, they can work backward from customer success AI insights and deliver what customers want without too much trial and error.
  • Integrating AI with people – The goal is to have all product team stakeholders: engineers, product managers, and product marketers read customers’ insights from the same script. This fast-tracks product launches and fast iteration from customer feedback.

What are the roles of AI in customer success?

  1. Improve customer retention
  2. Increase customer royalty
  3. Increase the customer lifetime value
  4. Improve customer relationships
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AI for Talent Acquisition teams

Fast-growing start-ups looking to hire can add a chatbot on their website for applicants to send in their documentation. However, this is the surface level in AI for talent acquisition teams.

Other worthwhile artificial intelligence recruitment tools for hiring the best candidates include

  • AI CV filtering tools to pre-qualify candidates.
  • Social candidates discovery powered by AI that scrapes through social channels to reach suitable candidates.
  • Using AI tools like Grammarly to write better job descriptions.

Benefits of using AI for recruitment

  1. Increase hiring quality using standard AI job-matching solutions. The goal is to hire happier and more productive employees.
  2. Save recruiters’ time from performing recruitment tasks
  3. Attract and interview relevant candidates.

AI for Team Productivity

Sales and support need tools to perform at their fullest potential. AI solutions like chatbots and virtual assistants empower teams to deliver twice as much using half the time.

For instance, our AI Bot for small and medium-sized businesses (SMBs) is designed with cloud contact center users in mind. We want to improve conversations, drive revenues and delight customers around the clock.

Want to explore AI for Team Productivity or take Aloha Bot for a test drive? Get a demo.

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