The Future of Sales: How Automation and AI Are Changing the Game.

The COVID-19 pandemic prompted many sales organizations to adapt quickly to buyer preferences shifting towards virtual and remote interactions, adopting hybrid work models and realigning their competitive advantages around building strong relationships while understanding clients as thought partners.

In order to be competitive in sales, Sales departments have to transform themselves digitally and incorporate the new technologies to provide value to customers and create a happy customer experience at all levels. This means cultivating innovation culture, staying agile and using data analytics.

AI-Driven CPQ

AI-enabled CPQ systems are turning out to be the solution to modernize sales and retain customers. Providing high agility, data-driven decision-making, AI systems are now emerging to take centre stage as they power sales transformation and customer retention.

Using machine learning, sales people can get the product/configuration, price/quote generation all automated — so they can spend more time on relationships and close deals.

As well, Next-Gen AI solutions enable businesses to optimise pricing based on market patterns and customer behavior so quotes don’t fall behind the margins. They can also see if there is any unmet upselling or cross-selling potential within an existing customer install base to upsell and cross-sell — especially important when usage-based and dynamic pricing is challenging legacy models. Moreover, Next-Gen AI solutions allows sales teams to browse hundreds of configuration options in seconds to build individual quotes – saving them valuable time while creating individual estimates.

AI-Driven Sales Analytics

AI Tools — Artificial intelligence helps in sales by automating boring tasks and giving teams insights. From prospecting to setting appointments and creating follow-up material to email marketing that’s been formulated and delivered by artificial intelligence, sales AI automates business and generates increased sales.

The sales analytics aided by AI offer enterprises with key customer data, competitive positioning and market dynamics that enable them to automate the sales cycle and forecast properly so that sales can be attained more effectively.

AI-Driven Lead Scoring

AI-based lead scoring – A great new use case for predictive analytics to assign leads scores automatically and eliminate human bias and maximize efficiency and productivity.

The prediction model learns from past conversions to figure out what leads were successful and which leads were unsuccessful and use that data to rank leads in relation to their chances of converting.

Predictive lead scoring is a lot different than manual methods, as it’s very fast, precise and constantly learning and updating predictions. It was intended to help salespeople leverage their experience and gut feeling by getting more time to value opportunities — so that they could hit their monthly objectives faster and easier.

AI-Driven CRM

AI is making CRMs into killer tools to enable sales teams to excel. From predictive analysis and automation, to customer data, etc. There are many ways that AI can be utilized to increase productivity and set the business up for long term development.

Machine learning and natural language processing-based CRM tools from AI automate customer segmentation, personalization, and marketing campaigns using cross-channel data. In addition, these AI systems can generate customer profiles from customer interactions and actions related to your brand as well as give tailored customer service via chatbots.

Artificial Intelligence based CRMs also help sales people in the discovery of upselling and cross selling possibilities based on historical data, anticipating future needs, behaviours, and trends — which allows sales team to make product recommendations for customers with high revenue and customer satisfaction.

AI-Driven Automation

AI automation is quickly changing from a technology into a critical business tool for organizations to operate better, run faster and make better decisions. In the right hands, a company can save a lot of money in the long run through automation of boring or time-consuming work that drains staff’s time.

AI chatbots can take care of the majority of customer service calls and eliminate backlogs while referring more complicated questions to human agents for processing, freeing up personnel to invest in higher-value tasks.

Machine learning lies at the foundation of AI BPO — so that systems can learn from data and make choices automatically, without having to explicitly program. This makes automated functions such as individualized marketing, ITSM resolution, supply chain optimization, and cost savings within supply chain possible. Implementation should be done slowly to not overtax the employees on new responsibilities and make sure everyone gets all the support they need to thrive.