Guide to AI Strategy for the Market Research Executive

A simple approach for a complex technology

Artificial intelligence is transforming market research. US companies are predicted to spend over $31 billion in 2020 to better understand their customers, their markets, their competitors and the perception of their brand. AI is fueling this increase in spending, up from $16 billion in 2019.

For organizations embracing digital transformation, it’s an exciting time. Digital transformation initiatives are integrating digital technology into all areas of the business, transforming how the business operates and delivers value to its customers. Since technology is rapidly evolving, this transformation is driven by a cultural change, not a single process or initiative, that requires experimentation, learning and failure.

Yet many US companies haven’t started a digital transformation initiative. For those in strategic marketing, PR, product management or product R&D in one of those companies, the words “AI” or “digital transformation” can cause frustration, confusion or fear.

Successful digital transformation initiatives are best undertaken as top-down initiatives, led from the C-suite or senior executive level. IDC estimates that 40% of all technology spending is focused on digital transformation, with the majority in the enterprise.

And many companies that engage in digital transformation are doing it out of necessity — because they failed to evolve.

Understanding the Role of Artificial Intelligence

One of the challenges in many digital transformation initiatives is that artificial intelligence, even at the business level, is still not clearly understood.

According to the Brookings Institute, “AI generally is thought to refer to “machines that respond to stimulation consistent with traditional responses from humans, given the human capacity for contemplation, judgment, and intention.”

That’s an academic definition. A layperson might define AI as a branch of computer science focused on building smart machines and programs capable of performing tasks. Which could be further simplified as follows: AI are computers that can “think”.

AI is not just limited to self-driving cars or futuristic robots. AI is present in many products and services we use today, and chances are, you’ve probably used it yourself this week without even knowing it.

For instance, have you done any of the following recently?

• Driven a car with adaptive cruise control
• Used your voice to direct Alexa, Siri, Cortana or Google Assistant
• Flown on a commercial airline (The New York Times reports that the average flight of a Boeing 777 plane involves only seven minutes of human-steered flight, which is typically reserved only for takeoff and landing.)
• Applied for a credit card or loan
• Used an email title predictor tool in email marketing software

AI works by combining large amounts of data with fast, iterative processing and intelligent algorithms, allowing the software to learn automatically from patterns or features in the data. It’s a broad field with a number of major subfields including:

• Computer vision
• Machine learning
• Deep learning
• Cognitive computing
• Neural networks
• Natural language processing

Every industry has a high demand for AI capabilities. Examples of common AI tools widely used today are chatbots for customer support and answering systems used for legal assistance, patent searches, risk notification and medical research.

Other examples of AI use in different industries include:

• Health Care — Providing personalized medicine and X-ray readings and providing reminders to take medication or exercise
• Retail — Personalized shopping recommendations and discussing purchase options with shoppers
• Manufacturing — Analyzing IoT data from connected equipment to forecast expected load and demand
• Banking — Identifying fraudulent transactions and fast, accurate credit scoring
• Market Research — Analyzing news articles and video at scale to interpret how the market is perceiving your brand (and here are specific use cases of the Rehinged.AI platform)

The good news is that, irrespective of whether you’re currently in a digital transformation initiative, startups and enterprises around the world are building new AI products and integrating AI into the existing products that you may already be using.

• CRM such as Salesforce has included AI features since 2016
• Google, Amazon and Microsoft products include many types of AI
• Banks and financial institutions rely on AI to determine creditworthiness and protect against fraud

Using the simplest definition of AI — computer programs that can “think” — there are thousands of applications to different areas of a business. In marketing alone, there are 63 ways artificial intelligence is transforming marketing. That’s why digital transformation needs to be driven from the top down — because AI initiatives need to be aligned with overall business strategy.

AI Strategy for Market Research

If you’re with a Fortune 500 enterprise, chances are you’re familiar with your company’s AI strategy. But for the thousands of other enterprises and midmarket companies who are grappling with the idea of how to leverage AI, here’s a simple approach that can help you determine how to take advantage of this technology.

1. Focus on Business Questions

Start with the business questions, don’t start by taking technology and looking for a problem to solve. Start by reviewing your business questions / challenges and finding the technology that delivers the solution. What is not working in your business? What issues or challenges are you having in a specific area? What are the hardest questions to answer in your business? Where are you spending money for people to complete repetitive processes manually? What important content, data or information about your market, brand and customers is not being read and understood by your team?

2. Understand AI Benefits

What benefits could AI potentially provide against your problem? Here are the three main groupings of benefits from AI:

• Speed — Machines don’t get tired and programs can process information faster than humans, for long periods of time.
• New Learnings — Gain insights that many humans would miss. Gain insights from the speed of algorithms.
• Accuracy — Machines and algorithms can make far fewer mistakes than humans.

3. Determine Actions

What coherent actions will you take? What resources will be a part of the project (people, budget, data, software)? Will you entertain the idea of building in-house, using internal or contract resources? Or will you look for products or services with AI to provide the answer?

The following diagram from Gartner outlines the essential aspects of AI strategy planning: data preparation, clear business cases, and experimentation/evaluation.

AI Strategy Reminders

If you don’t have the ability to have your company’s leadership initiate a digital transformation process, you can still take advantage of AI. Just look for the products and services by both leading vendors and AI startups that can solve one of your business challenges.

Always start with your business challenge — don’t just bring AI into your organization looking for a problem to solve.

Also, keep the following in mind:

• AI can make tedious tasks a thing of the past and can optimize your operation.
• Not every task can be replaced by AI or should be augmented by AI.
• AI is data hungry. The most common challenge with AI is data access, availability and quality. You need a lot of high-quality data to get acceptable performance and accuracy from AI.