Fundamentals of competitive intelligence: Competitor profiling

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Space307

10 min readApr 3, 2024

Competitor profiling: Part 1

This is the third article of our Competitive Intelligence series. We are the Space307 Strategy team — Head of Strategy Kirill Shikhanov and strategy analyst Artyom Khanganu. The first article touches upon the basics of CI and how we embarked on the Sauron project. The second article focuses on the competitive landscape. Don’t forget to check them out.

Today, we will explore competitor profiling and break down our approach to this task.

What is competitor profiling?

A thorough analysis of your competitors and their key markets is the second stage of competitive analysis. You have to know what players employ business models, product, pricing and marketing strategies similar to yours. As we continued improving the Sauron bot, our team members started requesting more information about particular brands. This interest prompted us to enhance the bot with superb graphics and practical solutions to gather analytics.

BCG Growth Share Matrix

We powered the update with the Boston Consulting Group (BCG) Growth Share Matrix. Suppose you already know your competitor’s business model and key markets well enough. For research purposes, let’s assume each market has a unique audience. This way, your competitor promotes a distinctive brand for each country in their portfolio. The BCG matrix provides a detailed analysis of this portfolio and helps you gain valuable insights to adjust your business or go-to-market strategy.

The growth share matrix is a table split into four quadrants, each with a unique symbol representing a certain degree of profitability: Question marks, stars, pets and cash cows. Each quadrant is one of your competitor’s markets.

The Sauron bot can generate a matrix for any player on our markets to help the team make swift decisions about where to focus our resources and capital to gain the most value and where to cut losses.

If a user requests the matrix, Sauron will send a PNG file and a transcript.

It takes about a minute for Sauron to generate the matrix, including gathering data, making calculations and building a chart.

Our version of the BCG matrix has two axes. The x-axis represents the market share value (the total of average MAU values for a year). The y-axis shows the market growth rate compared to the total of average MAU values for the previous year.

Two axes divide the chart into four quadrants. The exact size of the planes is different in each request and is defined based on the average values for each country.

Plotly, the open source graphing library for Python, allows us to use quality graphics, manage layers and adjust overlays and transparency levels when drawing charts. We color-coded each quadrant to make the chart easily readable.

Drawing graphs manually takes a lot of time, since you need to adjust the scale and sizes of elements and axes. Some teams employ BI systems. In our case, creating high-quality charts has become an automated process because Sauron registers values that can mess up graphics and posts them as text accompanying the matrix. We also added a flexible matrix grid.

Why do we accompany the matrix with a text transcript?

The text that comes with the matrix is an automatically generated list of countries with key metrics that are not featured on the chart:

First, the user sees the competitor’s entire market portfolio on the chart. The accompanying text gives them an opportunity to go into more detail and explore specific metrics and country rankings. The responses Sauron sends can be shared across channels and charts on Slack.

“By automating the process of generating charts, we contributed to effective competitor profiling. Sauron offers multiple ways to conduct competitor profiling and gather competitive landscape data. You can examine a particular market, check the key players’ info, switch to a different market and so on.”
Artyom Khanganu, strategy analyst

Be aware that factors like the business environment or geopolitical, social and economic changes are not reflected on the charts. It’s also not possible to combine information from different sources in one chart. To make sure our team receives comprehensive data, we introduced a couple more Sauron reports. One of them uses SWOT analysis — we managed to automate the method and recommendations the bot provides based on the results of the analysis.

Competitor profiling: Part 2

SWOT analysis

SWOT analysis is a strategic planning technique used to identify internal and external factors influencing the organization. These are:

Strengths
Weaknesses
Opportunities
Threats

We use SWOT to conduct competitive analysis, focusing on competitive intelligence and market data. By introducing SWOT, we managed to:

Combine data from all of the sources our bot uses.
Highlight crucial information featured in reports.
Provide recommendations and conclusions.

Our team identified 26 SWOT/CI triggers based on various market scenarios that can be unambiguously interpreted as strengths, weaknesses, opportunities or threats.

Suppose the Market position analysis defines the market as a near-duopoly (read more on market types here). In this case, the largest player is threatened by the second largest player. If we analyze the market leader, the system will assign the second largest player to the Threats quadrant.

If we analyze the position of the second largest player, the near-duopoly market will be an opportunity.

To introduce SWOT, we enhanced Sauron with two more features:

SWOT/CI trigger identifier
SWOT slides generator (the bot sends slides at the request of the user)

Triggers are calculated with a scalable function. It checks if the conditions of all 26 triggers are met using data from two sources (data.ai and Google Trends) and generates a list of particular triggers.

We designed a Figma template resembling marketing research presentations. This way, Sauron can send users corporate-styled slides with the specific information they request.

We also uploaded empty slides representing each quadrant (S, W, O and T) to Sauron. After the system identifies the triggers, the bot automatically fills the slides with relevant data.

The final slide design and content are provided by a function based on the Pillow Python library and our dynamic grid and layout. Below are some examples of the final slides Sauron sends to users:

As you can see, the Strengths slide features two triggers, while the Opportunities slide contains four. Here’s how we interpret the triggers:

S — market leader. Our competitor is one of the five players with the largest audience (1,000 users or more) in all countries listed.
S — strong search interest in the category. The player is among the top 5 players by search interest in the category.
O — chance to create a duopoly. Our competitor is the second largest player by audience in a fragile monopoly market.
O — decreasing market acquisition. The total install volume of all players in the category in all listed countries has decreased by more than 10%.
O — leading a growing market. Our competitor is one of the five players with the largest audience. The market has grown by at least 5%.
O — second-best in a duopoly. Our competitor is the second largest player by audience in a stable duopoly market.

The SWOT matrix helps assess competitors’ positions but doesn’t provide specific recommendations. To deepen the analysis, we tacked on the TOWS framework.

TOWS analysis

TOWS takes the SWOT analysis one step further to help organizations take action.

To get a feel for the framework, take a look at the chart below:

Classifying the markets a particular player is active in is a way for us to develop effective strategies to operate in those markets:

Maxi-Maxi strategy: Amplifying strengths to seize golden opportunities.
Mini-Maxi strategy: Seizing opportunities to offset weaknesses or turn them into strengths.
Maxi-Mini strategy: Employing robust strengths to deflect or overcome challenges.
Mini-Mini strategy: Tactfully sidestepping weaknesses and navigating clear of looming threats.

The system generates TOWS slides using SWOT patterns. However, one country can match triggers in multiple zones, so we added a prioritization feature to comply with the TOWS principles and make sure the same triggers don’t appear in different quadrants.

Prioritization prompted us to accompany the analysis results with recommendations on adjusting the company’s strategy.

Marketing Warfare strategies

The recommendations Sauron provides use the Marketing Warfare principles described by Al Ries and Jack Trout. These are strategies used by companies to deal with competitors:

The offensive warfare principle provides you with competitive advantages. Waging an offensive war, companies attack market leaders, second largest players or struggling companies.
The defensive warfare principle protects your competitive advantages. This strategy mitigates the risk of being attacked and the impact of attacks. It also helps a company strengthen its position.
The flanking warfare principle is perfect for operating in areas your competitor doesn’t care much about.
The guerrilla warfare principle is attacking, retreating and hiding repeatedly until the competitor abandons its position in the market.

After acquiring the data, Sauron adds it to the slides. We’re an international team, so the slides and the bot interface are in English.

The content of the slides reflects all triggers in all quadrants. The bot also generates a slide with the recommended strategy for the markets that made it to the final list. In the screenshot above, you can see that each row in the final table contains the strengths and opportunities of players in specific markets. We use two-letter country codes from ISO 3166–1 alpha-2 to represent countries.

Presenting data to the user

How do you present such comprehensive analysis to users? We organized the data into nine slides organized to allow users to spot strengths, weaknesses, opportunities, threats and recommended strategies immediately. Sauron sends these slides to users as PNG files in Slack.

Users can use buttons to navigate through the slides. The first slide indicates the competitor and the period being analyzed.

“Nine slides make up a 3х3 table. If you open the report on your desktop, you will see a SWOT matrix, with S and W slides in the top horizontal row and O and T slides in the first vertical row. There are four more slides with S/O, O/W, S/T and W/T triggers, and recommended tactics.”
Kirill Shikhanov, Head of Strategy

It’s easier to study the analysis results if the slides are organized logically. Users can forward the report to other team members by clicking the Forward message button.

BCG, SWOT and TOWS matrices help you quickly gather information and profile a particular player without missing out on important insights. Sauron’s reports allow our team to share and promptly discuss the data in a messenger.

The future of the Sauron project

We have some promising ideas in our backlog and will continue improving our CI tools and approaches.

More categories

A deep understanding of how the industry works helps us divide our competitors into custom categories and sub-categories. This way, our reports don’t depend on default classifications used by data providers. Our team makes decisions based on a classification system developed in-house. Now, Sauron splits over a thousand apps we regularly collect stats for into six categories. We plan to add more categories to make the process even more effective.

More data sources and marketing intelligence reports

Employing more data sources will help us avoid blind spots and raise the credibility of our reports. We’re currently exploring SimilarWeb as a web traffic data source. The challenge here is to efficiently compare data from different sources, considering all the relevant aspects. For example, sometimes, several brands from one publisher can’t be counted as one competitor in the rating.

Subscribing to reports

Since we launched the bot, the idea of allowing users to subscribe to a particular report has been in the works. The coveted Subscribe button is already on the way! Users will be able to subscribe to reports and have them sent to their DMs at specific times.

Employing OpenAI’s Assistants API

The beta version of Assistants API offers various scenarios of bot-user interaction. Some examples include human-like communication and requesting analytics directly (not via menu buttons). Another possibility is asking the OpenAI model to analyze a competitor’s historical data and answer user questions based on this data. However, the model’s access to the business context is limited. If we want to employ this tool, we’ll have to find a way to avoid hallucinations and validate the answers.

This series of articles covers the fundamentals of competitive analysis. Our team is already working on releasing new bot features. Maybe they will make it into our next article — stay tuned!

This series also features: