Have you ever played ‘Guess Who?’? It seems fun, but guessing is risky when it comes to market research. Marketing insights reduce the scope of guesswork by helping you identify the right course of action.  

With brands shifting to a more consumer-centric approach, the need and opportunity to build positive relationships with your consumers are immense. But consumer behavior is susceptible to change because of natural calamities, pandemics, recessions etc. Moreover, an average person is exposed to over 10,000 ads a day! Marketers must become more relevant, responsive and reflective to overcome these changes and grab their consumer’s attention.  

The problem with marketing insights today is the lack of –

1) Accuracy, 2) Actionability, and 3) Agility. Traditional market research methods require much manual effort. This makes it time-consuming, resource intensive and prone to human error. The adoption of AI in market research helps overcome these shortcomings.  

AI can stimulate marketers’ creativity and help them make quicker, better decisions so they can succeed in their roles. It can understand, analyze, and learn from massive and diverse volumes of data and facilitate natural connections between humans and machines. 

In this article, let’s learn how AI can step up for the lack of powerful marketing insights-  

Changing Consumer Behavior

Consumer Behavior is constantly evolving and changing. But the COVID-19 pandemic caused a massive shift in consumer behavior and consumption pattern. Lockdowns, financial crises and supply chain issues caused consumers to shift to online services and prioritize essential purchases. Let’s look at some of the most prominent consumer behavior changes in the post-COVID world.

Revenge Spending

Consumers suppressed the urge to splurge on products and services of their choice. According to McKinsey, 51% of consumers indulged in post-pandemic revenge spending.  

Brand Loyalty Disruption

Consumers increased their spending, but their patience has considerably reduced. For example, over 60% of consumers experienced out-of-stock items due to supply chain issues in the US. But most consumers did not wait for these items to come back in stock and instead switched brands.  

Social Media for Window Shopping

Consumers now choose to shop in an omnichannel way. 60-70% of consumers purchase both in-store and online. The influence of social media has grown, especially among young consumers.  

The Need for Consumer Centricity and Emotional Marketing

Marketing Insights come with an expiration date. Changes in consumer behavior are difficult to track, especially if it is sudden. Marketing insights need to be relevant, quick and to the point.  

A missed opportunity is a lost opportunity. If a marketer cannot implement insights on time, the validity of the insights expires. In this race against time, consumer-centricity and emotional marketing are your neon path lights, navigating you in the dark.

Consumer Centricity

“Client-centric companies are 60% more profitable compared to companies not focused on the customers.” - Source: Deloitte 

The best way to achieve customer centricity is by catering to the needs and opinions of the consumers. But traditional methods of collecting feedback are tedious, time-consuming and prone to bias.

AI-based market research platforms use technologies like Facial coding, Eye Tracking, and Voice AI to reduce these problems. With reliable feedback, your market strategy will be up-to-date with the changing mindset of consumers.  

Emotional Marketing

Emotions play a vital role in our lives. We use emotions to communicate our feelings, intent and thoughts. We are also subjected to and influenced by the emotions of the people we interact with.  

By aligning your marketing efforts to the sentiments of your consumer, you can –  

• Make consumers notice your product
• Influence their purchase intent and decision
• Improve brand recall
• Make them brand loyalists
• Improve consumer experience
• Increase consumer lifecycle

AI-based market research platforms provide metrics like attention, engagement and detailed emotional analysis. This helps you dive deep into the emotional journey of your consumers and connect with them.

Why Traditional Ways Won’t Fly

Old is not always gold. When it comes to market research, you need fresh insights. Traditional market research methods are- 1) slow, 2) time and resource intensive, 3) prone to bias, 4) require manual effort, 5) give no optimization recommendations, 6) data collection is post-exposure, and 6) only give surface-level insights.

The problems with the insights received through traditional market research methods are –

# Lack of Agility  

Unlike traditional market research, agile works on two simple mantras- Speed and repetition. As a marketer, you do not have the luxury of waiting. You are constantly racing against time and competitors. Insights received through traditional market research are almost always late and unavailable when required. It increases dependency on research teams and market research agencies which is unsuitable for breakthrough ideas.  

Related Read: What is Agile Consumer Research and How to Get Started?

#Lack of Accuracy  

Data data everywhere, not an iota to believe. Traditional market research is extremely prone to bias and human error. A go-to-market strategy is like a house of cards and unreliable insights, like the gentle wind.  

The problem with the lack of accuracy is that it is like carbon monoxide. You can’t see, feel, or detect, but it is toxic. For example-

In 1992, Pepsi decided to enter the expanding industry and launched Pepsi, which was clear. With sales of about $500 million in its first year, the drink known as Crystal Pepsi initially showed promise. Market analysis suggested potential, so Pepsi was unprepared for the ensuing consumer uncertainty. Customers questioned the healthiness of Crystal Pepsi and why a transparent beverage with a Pepsi-like flavour costs more.  

Pepsi’s market research phase is when they should have discovered this consumer engagement failing.  

Related Read: How to Reduce Bias with AI-led Behavioral Research

#Lack of Actionability

As a marketer, you want clear action items to follow. For example, you want to understand the best place for your ad placement. Imagine you get insights like “40% of Americans love watching movies”. This does not give you a clear direction. There are a lot of unanswered questions like- What type of movies? Where do they prefer to watch these movies? At what hours are they most active?  

Ad placements are expensive. Choosing the wrong time or location will be unsuccessful in attracting potential customers. Traditional market research fails to give these insights, making marketers often ditch data and go with their intuition.  

Related Read: Making Consumer Insights More Actionable with AI and SaaS

Getting Started With AI-led Marketing Insights

Facial Coding  

Facial coding maps the facial muscle movements to detect emotions and engagement. Our face is capable of making over 10,000 facial expressions a day. AI-based facial coding maps these expressions frame by frame using computer vision and advanced machine learning.  

Application

Imagine you are trying to evoke feelings of sadness through an ad. Using Facial Coding, you will be able to evaluate the efficacy and relevancy of the ad. You can determine the ad performance by making the suggested changes and ensuring you put your best foot forward.

Related Read: Facial Coding: What, Why, and How to Use Facial Coding in Marketing?  

Eye Tracking  

AI-based eye tracking is used to- 1) monitor what people choose to look at, 2) the directional path of the eyes, and 3) the frequency at which a particular element is being looked at. Most online research platforms use webcam-based eye tracking, reducing the dependency on hardware. It uses explicit eye calibration to develop a self-learning model.  

Application

Imagine in an ad test that you want to evaluate if people are noticing your brand logo. With eye tracking, you can analyse each element present within the ad in-depth.  

Voice AI

Voice AI technology is used to understand a person’s emotions, confidence and sincerity in-depth. It uses AI, machine learning, and natural language processing to detect and quantify the emotions concealed in speech acoustics and voice tones.

Application

Imagine you are conducting a focus group discussion. With voice AI technology, you will be able to understand if the respondents genuinely feel what they say. It will also provide automated transcriptions and translations, making data analysis easy.  

Use Cases for Marketers

AI-based technologies can be used for many use cases; let’s learn about a few here, taking this macadamia nuts pack as an example.  

Ad Testing  

Imagine you want to introduce a discount offer. But how do you ensure this will successfully grab the attention of your target audience? Using AI-based market research, you will be able to-  

• Segment each element to evaluate what works and what does not
• Compare your ads with your competitors’ with benchmarking scores
• Analyze the efficacy and relevancy of the ad  
• Get insights based on the visual appeal and engagement of the ad

Related Read: Behavioral Research for Ad Testing

Concept Testing  

Imagine you want to increase the sales of your macadamia nuts party pack, and you choose to highlight that it is completely ‘natural’. How will you know if it will make more people buy your product? Getting it printed on all packs and then regretting it is a no-go.  Using AI-based market research, you will be able to-  

• Validate your concepts pre-launch
• Reduce rework and production costs
• Make intelligent investments and de-risk big investments
• Foster innovation

Related Read: Behavioral Research for Concept Testing

Branding Research        

A brand is known by multiple elements- colour scheme, logo, characters, messaging etc. Imagine, if you were redesigning your timeless logo, wouldn’t you want to know if your audience would receive it well.  

GAP realised how important it is to get consumer feedback when their new logo only lasted a week! Instead of waiting to receive feedback post-launch, GAP would have been able to save millions on rebranding if it were pre-tested using an AI-backed research platform.  

Don’t be like GAP; use AI-based market research to –  

• Pre-test minor and major changes that associate with your brand
• Test messaging to convey the right brand equity
• Improve brand recall
• Identify purchase triggers  

Product Testing

Imagine you are trying to launch a new product in the market. How will you ensure that the pack design competes well against your competitors and will make consumers purchase your product?  

Many elements matter in a pack design- the colours, aesthetics, visual appeal, feel etc. But did you know that consumers spend only 1% of their time reading the content and 90% of their time on the outside packaging?

Using AI-based market research, you will be able to –

• Design a more attractive and engaging pack design
• Determine if consumers are choosing your pack using a virtual shelf test
• Identify purchase intent drivers  

Related Read: Behavioral Research for Product Testing

What’s in it for Marketers?

Every year more than 30,000 new products are launched, and 95% of them fail (Harvard Business School). Nobody wants their hard work to go in vain. AI-based market research is here to give you clear insights so that you can choose the best course of action. Testing should not be a one-time investment; it needs to be a habit.

AI-based insights can help in  

• Increasing the Marketing Spend ROI  

When a 30-second ad costs 6.5 million U.S. dollars to air during the Super Bowl, it must hit the sweet spot. Testing leads to perfection, but at a cost. Even though online research platforms are not free, they are an investment.  You get to put your best foot forward by making modifications based on the insights. Otherwise, we all know how ads can quickly go wrong and can cause a loss of millions!  

• Virality

With new forms of content like reels, TikToks, influencer-based promotions, etc., making viral content has become vital for gaining new customers. You can ensure that people will like what they see by testing your content before launching. Viral content is one of the best ways to boost brand awareness and increase brand recall. Knowing what kind of viral content best suits your brand can facilitate better click-through rates and increase your consumer base.  

• Creative and Channel Performance

Did you know 70% of marketers prioritize content quality over quantity? Quality of the content can be judged on two main parameters- 1) If it is relevant to the target audience and 2) If it contributes to revenue generation. To be able to choose the right content and make the right creative decisions, you need to know your consumer and the target market truly.  

AI helps you make the right choices and allows you measure and quantify your creative decisions. It also enaenables you to decide which marketing channels best suit your brand. This leads you to make intelligent investments using audience segmentation and targeting.  

Related Read: A Marketer’s Guide to Consumer Research

Getting Started

In today’s day and age, all you need is access to the internet and a laptop to conduct research. The adoption of AI has led to intelligent DIY platforms which use Facial Coding, Eye Tracking, and Voice AI to fasten your turn-around time by four times! With automated reports, an interactive dashboard and an easy-to-use platform, online research platforms are here to stay. They make you self-sufficient by reducing the dependency on your research teams and market research agencies.  

Adopting AI in your consumer research can seem daunting. But AI is not here to replace your consumer research but to modernize it. Online research platforms provide an end-to-end consumer research experience. With Quant and Qual research capabilities, you can run surveys, IDIs and FGDs better.

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