Post-Normal Market Intelligence

“Not yet omnium contra omnes.” That phrase nicks Thomas Hobbes in his masterpiece Leviathan, published in the 17th century. It means more or less 'everyone's war against everyone. For Hobbes, war or conflict is perhaps a natural life that is impossible to avoid. In the business world, some entrepreneurs may agree with a similar paradigm.

For a long time, businessmen have tried to take lessons from the science of war as the basis for winning the competition. The following two names are perhaps the most frequently mentioned: Carl von Clausewitz and Sun Tzu.

Carl Phillip Gottfried von Clausewitz (1780 – 1831) was a Prussian soldier and prominent military educator. Meanwhile, Sun Tzu lived in an era much earlier. He was a genius Chinese military commander who lived from 544 BC to 496 BC. Although both have military backgrounds, the two have quite different views.

This difference can be seen in the thoughts on war strategies they put forward in their respective masterpieces, namely 'On War' (Clausewitz) and 'The Art of War (Sun Tzu). Quotes from these two military geniuses might represent the difference in their views.

“War is the continuation of politics by other means.” Carl Phillip Gottfried von Clausewitz (1780 – 1831)

“The supreme art of war is to subdue the enemy without fighting.” Sun Tzu (544 – 496 SM)

Clausewitz's views tend to be more brutal and aggressive. In contrast, Sun Tzu represents a more diplomatic strategy. As a marketing person, I prefer Sun Tzu's opinion. Business competition is like war. That's why one of our Executive Education Programs this year takes the title Marketing Battle Plan.

But as Sun Tzu preached, wars can often be won without bloodshed. That's why companies need Market Intelligence. This strategy is how to win the competition without going through "bloody" conflicts. Once again, I would like to quote Sun Tzu's words regarding this matter: "If you know both yourself and your enemy, you can win a hundred battles without a single loss.".

You can get relevant data to develop sharper strategies with practical market intelligence.

WHY: DATA IS THE NEW OIL

Petroleum is an essential natural resource widely used for vital things. Because of the importance of oil, during the second world war, one of the things that caused Germany's defeat was the lack of oil supplies to fuel their combat equipment. Then, why does the phrase "data is the new oil" appear? The answer is, of course, clear. In this digital era, data mastery is very vital for business people.

Let's look at the following data. About a decade ago, a survey from Deloitte revealed that 49% of respondents thought data analytics helped them make better decisions. While 16% said data helped execute strategic initiatives better, 10% said they could improve relationships with customers and business partners using data. Another report from the same institution in 2020 also explained that data could increase productivity, increase sales and revenue, and facilitate the processes of a business. See how vital data is to your company!

In previous articles, I have continually emphasized the importance of creativity and innovation. Data is the foundation for both. Based on data released by EY , 71% of companies use insights from data and analytics to accelerate innovation, and 83% of respondents use data to help them innovate faster. Two examples of companies that are successful in leveraging this data are Netflix and Starbucks.

Netflix is one of the major players in the streaming and TV show industry. Undeniably, their current success is due to their familiarity with their customers, as demonstrated by their retention rate of 93%. Netflix captures user data such as time spent watching, preferred movie genres, and other data. This data is then used to recommend new shows to consumers and Netflix producers and executives.

Personalization is the key to growth in the digital age, and that's what Starbucks is doing. They use big data to create a better customer experience. Starbucks uses the app to collect data about consumers' most frequently purchased orders and suggest purchasing menus based on their preferences.

WHAT: HUMAN vs MACHINE

Let's talk about big data processing, then, of course. We will need the help of Artificial Intelligence (AI) to process it. With the rapid advancement of technology, is it possible that humans will no longer be needed to make decisions in the future? Is it possible that machines will do everything?

In the book Marketing 5.0, we emphasized that humans and machines have different roles and strong points from each other. Machines are more efficient in processing data and information, but humans ultimately have to make decisions. Machines can think convergently to find patterns from a data set, but on the other hand, only humans can come up with new ideas that were not thought of before.

Machines are very reliable in performing logical calculations based on programmed algorithms. Still, they lack the empathy to understand human emotions fully. Thus we can conclude that they are reliable for repetitive tasks and can be programmed quickly. In contrast, humans are designed to perform tasks that require a more comprehensive contextual understanding and reasoning.

In processing data, perhaps you are familiar with the NDIKW framework, which consists of noise, data, information, knowledge, insight, and wisdom. Noise is data with meaningless or incorrect additional information that needs to be discarded. This noise arises through human activities by communicating, disseminating information, and interacting digitally. Therefore, valuable data often overlaps with hoaxes.

On the other hand, data, information, and knowledge are the expertise of machines. Machines are excellent at quickly processing data that was not meaningful into information. In addition, machines can link various information to form knowledge that can be stored and viewed if needed. From the existing knowledge, it is the human task to draw relevant insights into the problems experienced. But above all, that shows the superiority of humans over machines is their ability to generate wisdom. It is namely making decisions that are not only based on aspects of logic and profit but also ethics and morals. From this, we can see that humans and machines play an essential role in data processing according to their respective capacities.

HOW: COMPETITOR AND CUSTOMER ANALYTICS

In the past, Kenichi Ohmae once said that to win the competition, a company must understand three things. The three are Customer, Competitor, and Company. He shortened it to 3C. I then developed this model by adding a fourth C, namely Change. So be the 4C Diamond model we always use to help clients analyze their business landscape. This model is the framework you need to do Market Intelligence.

You need to always pay attention to changes that occur so that the company does not miss the trend. These changes can be in the form of new technology, socio-cultural shifts, the issuance of new regulations, macroeconomic dynamics, or turmoil in specific industries. With technology, you can now get notified when there is an update on an issue.

So you don't have to look for those trends one by one. Let the trend come to you. Of course, you need the help of technology as an assistant to search, filter, and present these new trends in real time and continuously. But remember, as previously discussed, the information and knowledge must be reprocessed into insight and wisdom as the basis for decision-making. At this stage, you can no longer rely solely on technology. This situation is when you, as a human, have a role to play in making decisions.

Customer Analytics

The second aspect that you need to monitor the dynamics is the customer.

Is it true that today's companies know customers better than customers know themselves? For those who often shop online, you must be familiar with the recommendation system in e-commerce. E-commerce sites will usually feature products that are predicted to attract customers. If at first, you were only going to buy one product, you ended up checking out more products. That is because what was recommended was appropriate to your taste and needs.

Of course, not only in e-commerce, we can find recommendation systems like this everywhere. For example, on streaming platforms like Netflix and Spotify, subscribers are offered a wide selection of movies or music they predict they will like. When they are scrolling on social media, they are presented with product advertisements that are predicted to open.

These kinds of predictions are examples of what customer analytics can do. Using technologies such as AI and machine learning, companies can quickly collect, process, and analyze customer data from multiple sources. Knowledge gained from this process can help companies better understand customers and predict their movements.

The more you understand your customers, the more accurate your predictions will be about their behavior and desires. Furthermore, you can be more confident and focused in making business decisions.

Bernard Marr, an expert in AI and data, analogizes this phenomenon to tuna fishing. In the past, tuna fishing had an equal chance of success and failure. Many ships go out to sea with little knowledge, such as information about areas abundant in fish. Will the same location the next day still provide great results? Not necessarily, either.

However, as technology develops, the ability of seafarers to fish for tuna increases. With satellites and ocean sensors, they can monitor fish movements accurately. Commercial fishermen always compete to be up-to-date using the latest technology. Otherwise, they might go out of business because they lost quickly to other sailors in catching Tuna.

The situation is similar in business practice. Suppose companies do not continue to improve their ability to understand the behavior of their customers through data. In that case, they may be defeated by competitors who can offer more targeted solutions for customers.

Today's enterprises are not only expected to meet customer needs but also to anticipate and exceed them! Companies need to leverage data and analytics to create more personalized customer experiences to excel competitively.

Let's take a look at the stats: 91% of customers are more attracted to shopping from brands that offer them relevant offers and recommendations; 83% are willing to share their data if it means they can have a more personalized experience ; companies can increase revenue by 10-15% through well-executed personalization .

Regardless of the industry, customers will appreciate an experience that is timely, targeted, and tailored to their specific needs. Developments in analytics and AI allow companies to process data on a large scale and in real-time. So that companies can continuously anticipate customer behavior at every point of interaction in the customer journey.

So it's true, supported by technology such as AI, companies now seem to have the superpower to know what customers want, even before customers know what they want. However, with a superpower like this, companies have a huge responsibility not to misuse customer data. As a popular quote from the Spiderman movie, "With great power comes great responsibility,". As a human, our role is to keep the use of this technology from deviating from the moral aspect.

Competitor Intelligence

Competition in the business world is normal and necessary to win the market. Business is not made to compete but to sell 'solutions'. However, more and more business people appear in the market, like it or not, and like it or not, causing competition to occur.

Competition in business is a good thing because it can encourage innovation and continuous quality improvement. Knowing the ongoing competition also makes the company 'swift' in determining marketing strategies and tactics.

Before entering the digital era, a competitor analysis has been carried out in various ways, such as observing competitors' products in terms of packaging, variety, price, and even composition. It is also used to seek competitor information through available media, such as websites and news, interviews with customers of competitors' products, and interviews with suppliers, distributors, and industry experts.

These methods are usually done directly, either by observing the products in the storefronts of supermarkets and stalls or visiting related parties. Before the digitalization trend, competitor analysis required a great effort in terms of cost, effort, and time.

With the current digitalization trend, it's easier than ever to spy on competitors. The presence of competitors and their products on various digital and e-commerce platforms makes the competitor's footprint, which we need as data, very easy to trace.

Facing competition by knowing market changes and movements made by competitors is part of competitor intelligence (CI). Implementing CI means identifying risks and opportunities early while changing market conditions and taking action to adapt. CI data is in the form of all information about competing companies, including their business and strategies.

The trend of digitization has indeed made access to information about competitors easier. However, how do we process so much complex data into information and knowledge that is easy to understand? Data alone is not enough. Good data processing to become knowledge is very important in formulating strategies. In fact, competition in this digital era is becoming more stringent with the disclosure of information between business people and the amount of information received by customers.

Luckily for us, there are now many tools available to monitor competitors. Starting from simple tools we use every day, e-commerce can be a source for finding prices, product variations, and ongoing promotions from competitors. Then, online review sites can provide information on consumer responses to competitor products. If a competitor has a lot of good reviews, it can be a benchmark. However, what if there are a lot of bad reviews? Of course, it will be a business opportunity to fill the gap between consumers and competitors.

Today, social media is another powerful source widely used to monitor competitors. Through Instagram, we can see what types of content competitors upload and how often they upload and conduct online campaigns to interact with consumers. Through TikTok, we can see how often competitors hold live sales and find out how to offer products. The website is also one of the crucial resources that are widely used.

More complex analysis can also be done with the help of analytic tools such as Facebook Ads, Google Analytics, Ahrefs, SEMrush, Brand24, and many others. But again, the data is still mostly sourced from social media, websites, and search engines. The advantage is that it helps us determine which keywords are being searched and used. We can also analyze popular content, find out the audience reach of content, monitor accounts, and content engagement, and find out the top competitors of the keywords we use.

Analytic tools are beneficial for business people in monitoring competitors. But, we need to remember that those who understand the product and business the most are us, humans, as business people, and not machines. Therefore, in its implementation, humans must also have a good understanding of the business being undertaken and its competitors. Various types of competitors that appear in the market need to be faced with different strategies. After understanding this, machines and technology play a role in helping humans work and make decisions quickly and efficiently.

This article was published in Marketeers Magazine, October 2022 edition.