Chatbots for the Foodtech Industry: A Beginner’s Guide

By Anush Clive Fernandes / In Foodtech, Chatbot / October 29, 2020 / 5 Min read

Foodtech in India is poised for its second breakout. As one of the few industries that thrived post lockdown, foodtech has received a lot of attention – from users, investors and media alike. Today we discuss foodtech in India, what the future holds for it and how a foodtech chatbot can help the industry at large.

Opportunity

The past year has been rough, but the foodtech market seems to be bucking most trends.

Even as COVID-19 chips away at the best and brightest, the country’s infrastructure investments in the years prior has born fruit. Thanks to the increase in online users, powered by cheap hardware and cheaper interest, India’s middle-class market has been mobilized into an online ecosystem.

This, combined with the lockdown, has led to a massive increase in the demand for food delivery services.

Grocery e-tailer BigBasket said new customers on its delivery platform have risen 84% during a seven-month period – January to July. The startup also claimed the retention rate of customers grew 50% during the period.

Food delivery companies like Zomato and Swiggy have seen gains too.

In a report released in September, Zomato notes that the food delivery sector has recovered to pre-Covid levels in various markets and in some cases grown beyond the pre-pandemic numbers led by affluent locations. Swiggy launched new grocery delivery segment to add revenue streams.

Investors have poured billions into the Indian foodtech ecosystem. $10.8 billion, to be specific. And this trust has only grown with time.

There were a total of 8 investment deal in foodtech in 2014.

Skip forward four years, and there were 32.

Delivery-focused startups – BigBasket, Faasos, Zomato, Milkbasket, Swiggy and Freshmenu, etc, are the primary recipients of investor funding – receiving over 97% of investments over the past 4 years.

So how can a foodtech chatbot help these companies?

Problem Statement

For starters – There has been no shortage of challenges that foodtech startups have faced over the past few years.

From valuation markdowns and restaurant associations calling on banning the platforms to consumers losing trust in them and a slew of support related issues, foodtech has been getting hit on all sides.

Companies face daunting problems of scale in all facets of operations – quality, marketing, revenue, margins and support.

Customers are often disenfranchised by the industry as a whole. Issues related to discovery, tracking, transactions, routing and even safety of their products all tie into their lack of trust.

Most foodtech companies struggle with communication, above all else.

And the primary drivers of that are monetary i.e., support is expensive.

Food tech companies face two primary blockers when it comes to delivering excellent support –

  1. Volume
    Foodtech companies process hundreds of thousands of orders a day. And assuming an aggressive growth strategy, they often double or triple their volumes within months. This means that the customer support team, which has to grow proportionately with volume – is often engorged. This is incredibly expensive. It is also inefficient.
  2. Distribution
    Foodtech companies fall prey to unequal volume distribution. Simply put, a company like Fassos or Swiggy will see a dramatic increase in orders around mealtimes. It will conversely see a large uptick in support immediately after. Companies like Bigbasket see similar trends, with massive volumes of orders and support tickets occurring over weekends. This means support teams are overstaffed for when volumes are low but absolutely slammed for their peak hours.

Both of these problems amplify the challenges of delivering quality support, at scale.

Solution – A Foodtech Chatbot

What foodtech companies need is a means of support that’s –

  1. more effective,
  2. less income intensive,
  3. more interactive,
  4. easy to use
  5. easy to scale
  6. and automated.

Let dive into the principles behind why automation is key to support that scales.

The 80-20 Rule

In foodtech, 80% of all support queries come from a 20% dataset of possible questions.

Ergo, automating this 20% dataset frees up to 80% of your company’s support-related resources.

Using a foodtech chatbot allows you to tackle your customers most repeated queries, immediately. Because its automated, questions like “where is my order”, “my order is delayed”, “I received an incorrect product”, “my payment didn’t go through”, etc are answered with a first response time of only seconds.

With fewer queries taking up human time, your agents can focus on the complex queries that need their attention. This personalized touch improves customer satisfaction while bringing down turnaround time.

But what happens when you scale and more customers start requiring support?

Induced Demand

When companies scale up, their knee jerk reaction to parallelly scale support is to add more humans to the channels they’re using. Bigger call centres, more agents manning emails, etc.

But this doesn’t work out. More often than not, the problem comes back with a bite.

Induced demand is an economic principle that states when you provide more of something, people are more likely to use it. It works a little like this.

  1. Your call centre is operating at maximum capacity.
  2. As your company acquires more customers, your call centre struggles to keep up with the increase in volume.
  3. Poor/delayed support leads to unhappy customers who churn.
  4. You add more agents to the call centre to combat this.
  5. Phone support is now better and quicker because of more agents.
  6. Since it’s easier for customers to have their queries resolved over call, customers abandon other means and start using phone support.
  7. The increased demand soon overwhelms your call centre again.
  8. You add more agents to the call centre and repeat the cycle.

This is also the principle behind why expanding roads doesn’t reduce traffic.

Summary

In summation, here’s how a foodtech chatbot helps companies in the industry.

Better CSAT – Chatbots answer repetitive queries quicker, leading to more satisfied customers. They also allow agents to tackle more complex queries more easily.

Lower TAT – Automating support queries allows customers to self serve, leading to quicker resolutions.

Easy to scale – Moving from 10,000 conversations to 20,000 conversations doesn’t require any hiring, training or payroll. Just a click of a button.

Lower costs – All in all, a chatbot allows you to provide your customers with delightful support, at considerably lower costs.

Interested in getting a foodtech chatbot?

Talk to the team

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Anush Clive Fernandes

Content and Marketing, Verloop.io

Love Canines, Conversational Automation and Curry - Steph and otherwise.