Buyers and dealers often struggle to make sense of specs, product features and model numbers associated with manufacturing goods, especially considering most products look the same. This, paired with outdated, static and frequently ineffective search experiences, means manufacturing brands struggle to fix the search problem and help buyers find what they’re looking for. Marketing, distribution and commerce leaders need to recognize that they cannot solve today’s problems with yesterday’s strategies or technology.
Research highlights that 70% of manufacturing buyers knowingly admit that their expectations are high, a further 62% demand more convenience and 58% expect a digital experience. Delivering a search experience which replicates the best elements of human interaction across digital channels is no easy feat.
Search experiences have not changed in nearly a century
The search experience we are accustomed to, filling out a box or selecting specifications from a filter feature, is nearly a century old. It was not built with customer satisfaction in mind nor has it transformed with our increasingly digital world. Manufacturing brands need to leverage technology that adapts to buyers, not the other way around. This is what AI conversational search does - offers a more intelligent and effective way to help customers narrow down search to a select few results that are actually relevant to what they are looking for.
For example, visitors to the Husqvarna website are faced with five simple, tailored questions to establish which product would be best suited, based on experience, workload, and what particular job they have in mind. From there, they are given a recommended product set to based on their answers. This eliminates the need for customers to self navigate, and reduces complexity by providing a search experience that goes beyond keywords.
From keywords to conversations
It’s well-reported that manufacturing organisations are struggling to differentiate products within an ever-expanding competitive market, which causes many to expand their product offerings. But, given that choice doesn't always equal conversion – how can manufacturing brands increase engagement and drive conversion?
The fastest way is to transform the search experience, moving from 'keyword' to 'intent'. The intent-centric model will help manufacturing brands to better understand what their buyers are looking for – enable them to spot opportunities for bundling, price comparison, price suggestions and more engaged customers will lead to repeat business or upsell opportunities
Buyers need help translating the tech specs, features and functions that feed traditional search experiences into a language they can understand and engage with - something which they can understand. And, the easiest way to engage with customers is simply...by having a conversation.
As an example,industrial supplier 3M wanted to make the process of buying Personal Protection Equipment (PPE) easier and faster. By installing conversational search tools on it’s website, 3M not only engages buyers in a conversation, asking the right questions to narrow down thousands of options to the perfect shortlist of products based on unique usage, they can also use their search experience as an internal training tool to keep all their reps and channel partners up-to-date on the latest products. The result? Buyers that are confident that their selection is compliant, their workers are safe.
Leveraging new emerging technology is a key focus to ensure manufacturing brands are recognizing the intent of buyers in the moment and, rather than leaving them to self-navigate their website,are engaging them in a conversation. Using AI, machine learning and NLP (Natural Language Processing) is the only way to translate SKU data into a language that is needs-based, easily understood and actually helps customers find the products they’re looking for.
Changing the buyer journey in this way will ensure manufacturing organisations can keep up with the growing demands of the industry.
Digital CX with a human touch
AI helps brands in the manufacturing industry to bring the best elements of assistance and guidance to digital. Unlike a human assistant, leveraging machine learning and algorithms mean you can gain critical insights behind sales performance to learn who is buying what, and why. Using AI to deliver experiences that feel “human” across digital channels may seem contradictory, but to remove friction in the search experience, especially at scale, requires the use of emerging technology.
The use of sales performance analysis allows brands in the manufacturing sector to monitor individual products and inform stock rotation, product development or retargeting efforts - but sales performance doesn’t actually tell us very much. If a particular model of camera sells more - do we know why? What would it mean for your organisation to actually uncover the ‘why’ behind the ‘what’?
Uncovering the data blindspots that power product preferences such as ‘who is buying?’ ‘what are their product preferences?’ will quickly separate the front runners from the rest of the market. The best will even learn to predict customers’ wants and needs, creating the shortest and most frictionless path to Understand and act upon buyer intent to increase purchase confidence by 81%.
Why it’s now or never.
AI-driven online conversations allow manufacturing brands to stand out from fierce competition and offer buyers the quick and convenient paths to purchase that they demand. The days of buyers calling an account manager and relying on a personal recommendation are numbered, and the future of the manufacturing industry is rapidly moving to favour a digital (and scalable) experience.
Creating a digital experience that delivers the hallowed elements of B2C ‘human’ engagement may sound contradictory, but it isn’t. Investing in technology that allows buyers to feel like they are understood and being guided as part of a conversation win the race. While the industry may not have historically led the way in customer-centricity, this will change in 2020 and beyond.
