AI data analysis

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Artificial intelligence paired with machine learning, automation, natural language processing and big data analytics can help to boost business and brand performance in an ever-competitive ecosystem.

In March 2020, when India announced a national lockdown to contain the Covid-19 pandemic, several traditional brick and mortar retailers had to shift to digital retail channels overnight. Most were unprepared for this and were forced to shut shop, being unable to cope with the huge hit to their margins.

However, this wasn’t the case for all brands. Brands that already had a strategic online presence in place were unknowingly prepared for the pandemic because when consumers turned to the internet for every little transaction and query, they could address those without making drastic shifts to their existing customer experience management methods. In this process, they could also understand, evaluate and extract insights from customer behavioural data, where technologies like Machine learning and Artificial Intelligence came to the rescue. Using these technologies, brands could sift through the unstructured data and garner actionable insights to formulate effective brand engagement and sustainable growth strategies.

Moreover, many put AI-powered chatbots at the forefront of answering consumer queries to ease off the burden from their contact centres where the work increased tremendously in volume and created a cost-effective way to engage, manage customers and gain, consumer confidence as well as brand loyalty.

The evolving landscape

As per an Akamai report, global internet traffic grew by 30% in 2020 with a huge uptake in social media during the pandemic-induced lockdowns. Moreover, according to research reports, 32.8% of retail sales now take place online, which accounts for roughly one-third of the purchases made.

The age of COVID has increased the role of AI-based SaaS models that work with big data automation, analytics, and response management. For a leading name in the e-commerce industry, AI was the solution to enhance the company’s overall growth. The firm began to employ AI and deep learning in its website’s recommendations to gather granular customer insight.  The result? The firm’s recommendation engine now drives about 35% of its total sales.

How AI can aid in social listening

According to Gartner, AI-derived business value will triple to nearly $4 million by 2022, and customer experience will be central to this growth. As enterprises delve into AI-predictive insights for enhanced brand management, the next derivative would be to know who your customers are, what they want, say, or feel about your brand, and what particularly makes them consider a rival brand.

For instance, a popular automobile brand was monitoring the success of their car launch when a curious discovery was made revealing women to be more interested in the variant to be launched. This revelation led to the brand retracting its original marketing campaign and relaunching it, this time thoroughly positioning the car as a women-oriented product.

A deeply explored branch of AI today, Natural Language Processing (NLP) can also be a significant driver of marketing and competitive intelligence. Using NLP, a leading SaaS company decided to develop and deploy an AI-powered Interactive Voice Response (IVR) System to improve the accuracy of its customer service phone system. With an extremely powerful AI-powered agent in place, the company was well-positioned to anticipate their customers’ unique needs while reducing the churn rate and the time spent by a customer on hold.

AI Tech for Effective customer experience management (CXM)

With limited physical interaction, tech integrations such as CRM (customer relationship management) are getting more advanced in order to cluster and classify important customer data available in the public domain.  For instance, a popular beverage brand implemented robust CRM software, which allowed the company to have instant access to important customer insights and behaviour. This in turn, helped them to hit their targets and deal more efficiently with queries and complaints.

When NLP and Machine Learning (ML) come into question, smart bots become more humanized, enabling them to not only answer routine customer queries but even more targeted ones.

Competition benchmarking to boost brand performance

In today’s fiercely competitive business landscape, one of the best promises social listening gives brands is a thorough understanding of how their competitor is performing in the ecosystem. For instance, the widespread popularity of a popular console brand can be credited to the firm’s relentless effort in finding online conversations related to gaming, gamers, and the brand itself. Further facilitating their online presence is the use of creative responses to engage their audience.

Furthermore, beyond listening to social chatter on digital channels, a digital command centre will further help brands to pull in data which when translated into actionable insights can improve market research, offer better customer support, and drive sales.

In conclusion

What is worth pointing out is that there is no alternative to a unified, streamlined platform converging AI, ML, big data analytics and automation to offer complete customer experience management. Organizations which adopt this single AI-powered SaaS platform approach have been able to strengthen their digital foothold while simultaneously bringing brands and customers closer. The result of this is online visibility, better customer engagement and powerful analytics for relevant business metrics. This in turn leads to better trend forecasting, astute competition benchmarking, and of course seamless customer experience management.

 

The author is Shubhi Agarwal, Co-Founder and COO Locobuzz Solutions.

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