What the original iPhone was to the smartphone industry, OpenAI’s ChatGPT may be to the world of advanced AI chatbots. From long waiting queues to record-breaking sales numbers and website traffic, the parallels are there for everyone to see. With over a hundred million monthly active users in January 2023, GPT-3 became the fastest-growing consumer application in history. If initial impressions of the recently unveiled GPT-4 are anything to go by, this trend will continue to grow stronger. Professionals across industries are hopping onto the bandwagon. Be it programmers trying to optimise code, writers trying to get over a block, or lawyers trying to hastily draft last-minute legal documents, everyone seems to be benefiting from OpenAI’s suite of advanced large language models (LLMs). Justifiably so, given the vast array of applications they have demonstrated huge promise in, within such a brief period.
Interestingly though, one particular group of professionals who have flown under the radar despite the massive untapped potential ChatGPT brings to their field are marketers. They may not be the most obvious choice for those covering developments around the space, however, a deeper look at the facts of the matter can reveal an abundance of endless opportunities—some that may well and truly lead us to reimagine MarTech as we know it.
Traditionally, business processes, from lead generation to customer support, have required varying degrees of manual intervention. Apart from being inefficient and laborious, it can often take away skilled resources from higher-priority tasks resulting in lacklustre end products. According to a report by Ascend2, 65 percent of marketers say they have all the MarTech tools they require, but less than half of them (31 percent) fully utilise what they have. This points to a problem within the status quo—one that could likely be bridged by AI-enabled LLMs such as ChatGPT.
For starters, ChatGPT holds the potential to push the boundaries of personalised messaging beyond anything that’s come before it. Now, GPT-4’s multimodal capabilities mean that marketers can utilise it not only for personalised text-based messages, but also for analysing multimedia, building functional websites from pictures of basic UI sketches, or finding common threads between disparate campaigns to better cater to their audiences. Compared to GPT-3, version 4 significantly lowers the amount of time between receiving prompts and delivering results. There have also been massive strides concerning the volume of words it can ingest, but improvements in GPT-4’s ability to understand the subtext and tone of certain tricky conversations are yet to be evaluated. That said, the prior experience would dictate that apart from the occasional hiccup, it would be able to uphold these interactions in an organic and almost human-like manner.
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In an era of hyper-personalisation, those that fail to meet this expectation are at a significant disadvantage from a CX standpoint. This was highlighted by McKinsey's report that 71 percent of consumers expect companies to deliver personalised experiences, while 76 percent get frustrated when this expectation is not met. With ChatGPT, brands and businesses that may have otherwise buckled under this ‘pressure to personalise’ can now roll out such features at modest scales without breaking the bank. By moving away from generic, one size fits all messaging, and focusing on contextual communication, brands can build meaningful digital relations and increase customer engagement—which ultimately will help drive brand loyalty. Even in its most basic form, ChatGPT could be deployed as a more advanced customer support chatbot. We have already seen glimpses of this with Intercom announcing ‘Fin’, a GPT-4 powered customer service chatbot that requires zero setups and understands complicated support tickets without human intervention.
When a campaign calls for it, marketers must think outside the box to express themselves via creative and diverse strategies. A prerequisite for this is the ability to rapidly test contrasting methodologies, and refine the ones that produce the best results. The operating word here is “rapidly”, because if this process takes too long, it may lead to noisy data, yielding inaccurate and imprecise results.
ChatGPT’s ability to receive a prompt and almost instantaneously output a usable result is game-changing. Imagine marketers looking for options for ‘what message to send’—an age-old problem within the field—who can now simply ask ChatGPT for variations on the copies their content team came up with. At scale, this kind of iteration can be gated behind the amount of capital and hours it usually costs. But the arrival of ChatGPT frees up valuable resources, enabling marketers and their teams to dedicate time to business-critical tasks like strategising or deepening pre-existing customer relationships. The fact that marketers can gain so much value from an inconspicuous chatbot raises an interesting point about the democratisation of MarTech today.
The feeling of disappointment that sets in when one realises they are speaking to a chatbot instead of a human is one that most can relate to. This is a major problem area within MarTech, but the aforementioned points show how ChatGPT can go a long way in ironing out these issues. As a customer who has dealt with traditional chatbots myself, the ones that come across as stoic, robotic and cold, dull the experience—regardless of whether they manage to solve my issue. Which is not to say anything about how they usually cannot, and refer me to a support rep anyway.
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Universally, if chatbots seemed more personable and expressive, customers would likely report higher-quality B2C interactions. When individual customers feel their issue was resolved compassionately, they feel cared for. Brands that sow these seeds of goodwill are bound to see them flourish into tangible metrics such as improved review scores and increased volumes of voluntary data sharing. But most importantly, it can strengthen the relationship between the customer and the brand organically. Integration of LLM-powered tools, especially within the domain of customer experience, could single-handedly raise the bar for customer interactions going forward—taking delightful automated customer experiences from a rarity to an expectation.
ChatGPT 4 is emblematic of the race to the next biggest LLM that was sparked by its predecessor—GPT-3. With competitors like Google’s Bard scurrying to enter the fray, there is no doubt how badly ‘Big Tech’ wants a share of that LLM pie. And if there is one thing that everyone should be excited about, it is competition.
With the future of LLMs looking bright, its integration with MarTech is bound to bring countless benefits to marketers looking to stay at the bleeding edge of technology. Imagine if ChatGPT were to be integrated into MarTech databases. Its NLP prowess could potentially lower the time and effort required to narrow down petabytes of data into smaller actionable data sets that meet certain criteria as opposed to traditional Boolean searches.
It’s not every day that a technology rolls around and single-handedly makes verticals within marketing, communication, and content creation more accessible. So when it does happen, due credit is imperative, and the plaudits are deserved.
Simultaneously, it is also important to realise that ChatGPT, like any other breakthrough technology over the past decade, needs time and refinement. For brands that over-rely on their capabilities, a reality check is in the works—be it through unavoidable human errors or undiscovered glitches within the technology itself. At the end of the day, it is just another weapon and not the entire arsenal.
The writer is co-founder and chief product officer of CleverTap.
The thoughts and opinions shared here are of the author.
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