How to start utilizing AI right now
Blog: BPMOnline Blog
AI claims to solve a lot of problems and provide even more benefits for businesses. Autonomous vehicles and online bots sounded dreamlike just a short time ago. But today is the time when each and every business is able to take advantage of the AI technologies with no need to integrate those for months. And this is how companies can swiftly adopt and start running AI-charged tools in all sectors of their businesses already today.
AI for Marketing
Lead scoring is a great example of how Ai is able to take prioritizing and managing leads to the next level. First off, AI tool is analyzing the sales and marketing database to study how the perfect client “looks like”. This will help to shape a pattern – the base of the scoring system. As a result, contacts that have characteristics of a “successful” lead will get a higher score. This will not only help sales prioritize communication and show better performance, but also provide insights into marketing for continuous delivery of the high-value leads.
AI-powered segmentation is another highly useful tool for boosting the productivity of marketing. Audience segmentation is critical for implementing personalized marketing strategy. But that’s not a one-time project and requires a lot of time and resources. And still, when done manually, it’s hard to keep it fresh. AI-based customer segmentation engine uses different analytical capabilities like behavioral tracking and predictive analytics to detect the most suitable customer groups. This leads to a number of benefits including keeping customer data clean and structured, maintaining highly personalized communication with contacts across entire customer journey resulting in the increase of marketing ROI.
AI for Sales
Predictive next best offer/best action is highly useful for sales reps to be highly proactive and appropriate in their communication with prospects.
It uses predictive modeling based on historical data to recognize actions that are most likely to lead to conversion to sales. AI is also responsible for identifying missing actions within accounts and recommending them to sales reps. Therefore, a better sales rep productivity is observed, a higher close rate of deals and an increased revenue.
Intelligent process analysis/optimization is a life-changer for C-level executives. AI is improving the processes, while they take time to focus on managing their staff. Based on predictive process analytics, this tool allows for running tests on potential changes and see which will have the best outcome. Adoption of intelligent process analysis enables faster and more reliable processes optimization; improvement in sales team performance; improved process adherence by sales reps; and greater revenue attainment.
AI for Service
Smarter knowledge management is a highly actual tool to help customers get relevant information no matter if they use the right terminology or not. AI tools based on deep learning and natural language processing are already solving this problem. This doesn’t just apply to customer-facing experiences; it can also help service teams find answers to questions faster and more effectively as well. Among the advantages are keeping staff up-to-date, faster time-to-resolution for self-service and service reps, reduced service headcount, etc.
Intelligent case routing and process management is a tool for automating and smartening up currently manual processes of routing and handling services cases. Using machine learning and natural language processing, as well as sentiment analysis and predictive modeling, incoming emails, support tickets, chats, and similar service interactions, will be able to be read, understood, routed, and escalated automatically. Implementation of intelligent case routing results in reduced call and issue resolution time, improved customer satisfaction and NPS, shortened customer support cost, reduced service headcount, and improved customer experience.
How to Get Started with AI Now
There is no one-size-fits-all answer to getting started as it largely depends on the state of technology in your company. You might want to focus on the most stable and predictable processes first since they will provide a solid baseline and enable you to clearly measure success. Alternatively, you might look to AI to help jump-start digital transformation in your organization and go after the most broken processes first. Either way, start with clearly defined use cases where results will be easy to measure so you can avoid scope creep and over-investment.