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How Can Data Analysis Benefit Organizations?

Pâmela Seyffert — Thu, 13 Apr 2023 10:16:05 +0000

Every day, we generate a significant amount of data online. Related to our personal or professional life, these digital footprints are collected through social networks, websites, platforms, among others. They provide important information about who we are, what we do and how we behave.

Therefore, in recent years, Data Analysis has become essential for organizations, as it reveals important characteristics of their consumers and competitors. However, much of this information is still not analyzed with a strategic eye and ends up not contributing to decision-making.

In a digital transformation scenario, corporates can no longer waste time with superficial and incomplete analyses. It became vital to develop a mindset oriented towards numbers and their potential for revelation. Therefore, we will discuss below the concepts, tools and importance of Data Analysis for the development and evolution of organizations.

Emotion x Reason

Do you make decisions intuitively or do you prefer to use analytical tools to support them? It is known that the experiences accumulated throughout life and business are still very valuable. However, with the high level of competitiveness in the current market, the use of Business Intelligence tools is essential – which organize information and optimize the data interpretation process.

Data Analysis consists of a process of inspecting and modeling the data collected. Its main objectives are to monitor, reveal relevant information (quantitative and qualitative) and point out business opportunities and weaknesses, supporting decision-making in organizations.

We can use Data Analytics in different contexts: Business, Science, Academy. In addition, this process has many approaches and techniques. In the contemporary business universe, Data Analysis has gained prominence by transforming routine decisions into scientific diagnoses, which help corporates and people to work smarter and more effectively.

Numbers, Numbers, Numbers

For the statistician John Tukey, Data Analysis is related to the techniques to interpret the results, since it includes the planning of data collection to make the analysis easier and more accurate. Mathematics and statistics are examples of mechanisms that help to apply this concept in the practical routine of corporates.

The term Big Data is relatively recent and, therefore, does not appear in most statistical dictionaries. This data is varied and has a high volume and can even be created in real time. Thinking about that, it is important to examine what are the tools that can help in the analysis process of organizations so that the competitive advantage becomes a business reality.

Currently, there is a wide variety of Data Analysis tools available on the market. Each of them has different languages and objectives, so it is important to consider the statistics and coding knowledge of the professionals who will use them. Below, we present some of these options.

Power BI

Power BI is a Microsoft business analysis service, focused on providing interactive visualizations and Business Intelligence resources – which help create indicators and generate reports, capable of facilitating decision-making.

This tool has a simple interface and allows each user to create customized reports and dashboards. This set of services also facilitates data accessibility, which can be viewed both on the local network and in the cloud. This means teams can work collaboratively and remotely.

Power BI has integration with Excel and custom and pre-built data connectors. This option also allows real-time access monitoring, helping to discover and share insights through internal Artificial Intelligence (AI) functionalities.

Tableau

This analytics platform features intuitive data exploration. Therefore, it can be used by analysts, IT professionals and executives. The tool has a simple design and interface, and its main attraction is the transformation of raw data into visual graphics.

Tableau supports cloud or on-premises storage. In addition, it provides the connection of different types of data and sources in the same report: spreadsheets, SQL database, Big Data, Google Analytics, Salesforce among others.

Google Analytics

This tool is one of the most popular on the market, as it helps the user through the steps: tracking, monitoring and reporting on traffic. Through it, it is possible to analyze the organization’s data in a single place. Like the other options, Google Analytics is focused on assisting in decision-making.

This option allows you to check marketing performance, that is, it is an important ally when monitoring business results to find opportunities and weaknesses. By using it, you will be able to better understand the behavior of your visitors.

Validating Ideas

There is a saying that what we cannot measure, we cannot improve. Thus, we found that data culture goes hand in hand with access to information. For this, the democratization of the collected data must be an important pillar within the organization.

When data becomes available for consultation and analysis, employees begin to use them in their decision-making routine. In this way, everyone ends up developing strategic work through actions with a collective impact, as information has crossed the borders between sectors and is now part of a holistic plan.

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Product Metrics: attention to data

Pâmela Seyffert — Tue, 23 Nov 2021 10:58:48 +0000

An important characteristic of the transition from a Project-based Culture to a Product-based Culture is the way to measure success. While in the first one we measure the fulfillment of the classic triangle of scope, cost and time, in the latter, we define product metrics related to the business, which prove the effectiveness of actions and the execution of objectives. But what metrics are these? Currently, there are several options of frameworks that can be used to analyze the performance of products. In this article, we will cover some of them.

Key Performance Indicator (KPI)

As the name says, the KPI is a Key Performance Indicator. There are hundreds of metrics that can be measured, but that does not mean they are all important to your business. KPIs are precisely those relevant indicators that need to be observed and analyzed, as they demonstrate the performance of strategic actions and initiatives. They are valuable because they assist in the decision-making process, confirming or refuting tested hypotheses. The best way to choose good KPIs is to think about how they relate to your objectives. If you want more people to use your app, for example, there is no use watching the number of followers on your Instagram account. One option, in this case, would be to evaluate the conversion rate of the “download app” button on your landing page, associating it with the rejection rate, which indicates how many people have uninstalled the app. Remember that looking at the wrong indicators can result in wasted time and money! Avoid the well-known vanity metrics, which are numbers that you can keep track of, but which should not influence decision-making.

Objectives and Key Results (OKR)

The model that supported Google’s growth is still used today by many Silicon Valley companies. OKR sets targets to be reached and objectives to be accomplished through the achievement of key results. The objectives must be clear and known to everyone on the team and must be stated so that people understand their impact on the business. The key results, on the other hand, need to represent the achievement of objectives effectively, and here it is even possible to use KPIs. Its simple and efficiency-focused approach makes OKR an excellent alignment tool since everyone knows what to do and what results to expect. For example, your objective might be to increase the number of transactions carried out through your payment platform by acquiring new customers on social media; and your key result could be reaching 10,000 transactions per month of customers converted by Social Media Marketing.

North Star Metric (NSM)

A guiding star is one that indicates a direction, that guides a path. That is exactly what the North Star Metric framework proposes. Through it, there is the definition of a crucial metric that focuses on business growth. It must be disseminated among all teams involved with the product so that everyone can connect in search of the same “north”. NSM expresses value and represents vision and strategy. Its objectives are to facilitate alignment and communication between teams; prioritize and accelerate the decision-making process, and encourage concentration on the impact generated by the product and on sustainable growth. For example, the number of customers completing their first purchase on your e-commerce website might be a North Start Metric. Suppose this number is five a day: what are the actions that will be taken towards this objective? Which ads will the marketing team run? What layout changes does the design team propose? Has the customer service team identified the biggest difficulties or complaints from potential buyers?

Pirate Metrics (AAARRR)

Awareness, Acquisition, Activation, Revenue, Retention, Referral: these are the six metric groupings in Pirate Metrics. This framework proposes these categories as possible to be analyzed, according to which aspect of the business you want to measure. Each of them is associated with a moment in the customer’s life cycle and, therefore, helps to identify areas for improvement – aspects that must be worked on in order to improve the product’s performance.

Awareness: The users’ first interactions when they are becoming aware of your product. Visits, Click-through Rate (CTR), time on the page, and pages per session are examples of metrics.
Acquisition: The users have given you their data and now you know who they are. Conversion rate per visit, engagement rates on social networks, and opportunities generated are important.
Activation: You know who the users are and they have effectively adopted your product – you are now on the onboarding stage. This category is most common for SaaS products and includes metrics such as the number of subscriptions, the average time between subscription and active usage, and Product Qualified Leads (PQLs).
Revenue: The users, in addition to being active, became paying customers. Monthly Recurring Revenue and Annual Recurring Revenue are the main metrics for this category.
Retention: Now that users have become customers, the important thing is to understand how loyal they are to the product. Retention rate, payback time, and customer satisfaction are essential product metrics.
Referral: Now that customers are loyal, they start to act as promoters of the product. Metrics such as sharing on social media, reviews, and recommendations can be analyzed.

Sales Funnel

We couldn’t wrap up this part of the article without talking about the Sales Funnel: It is a tool that allows you to analyze your business’ conversions. At the top of its structure are the visitors, those people who discovered and viewed your product; then the leads, which are people who, after discovering your product, took some action (such as filling out a form or requesting contact) because they considered it a possible solution to a problem; opportunities are those leads that effectively see value in your business and are willing to pay for it; and customers are the buyers, who have gone through the entire Sales Funnel and end up being converted. But what does this have to do with product metrics? To monitor the health of your business through the Sales Funnel, several metrics should be considered. They relate to the different levels of the funnel.

Interaction Metrics – Top of the Funnel: How do visitors and leads interact with the product? What are the hot zones? How does the usage journey work? Pageviews and click-through rates are important.
Performance Metrics – Middle of the Funnel: Can leads that have taken action actually become opportunities? Are they more interested in your content or in your product? The conversion rate of a series of buttons can be observed.
Return Metrics – Bottom of the Funnel: How many visitors became customers? How much was necessary to invest to win each customer? Return on Investment (ROI), Customer Acquisition Cost (CAC), and Customer Lifetime Value (CLV) are critical metrics.

What Are The Main Product Metrics?

We explored some Frameworks that help define common goals and product metrics, such as KPIs, OKRs, NSM, Pirate Metrics and Sales Funnel. But what metrics are these? We will address the most common metrics in the universe of digital products below. But first, it is worth noting: actionable metrics are those that effectively measure the success of the digital product or service, as opposed to the vanity metrics that can be observed but should not influence decision-making. The number of registered users in an app, for example, is a vanity metric, while the number of active users is an actionable metric. Remember this before choosing the best indicators for your business.

Customer Acquisition Cost (CAC)

The Customer Acquisition Cost defines the average investment required to acquire a new customer. The CAC is important for studying the feasibility of a business model and also for evaluating investments in the marketing of products that have already been launched. It is important to note that depending on the objective, the calculation of the Customer Acquisition Cost may vary:

To evaluate investments in marketing, the following simplified formula must be used: amount invested in acquisition marketing (AM) divided by the number of new customers acquired (CA) – CAC = AM/CA.
To study the feasibility of a new business, the use of the intermediate formula is recommended, adding the amount invested in acquisition marketing (AM) with the cost of the sales and marketing teams (ST), and dividing them by the number of new customers acquired. (CA) – CAC = AM+ST/CA.

Customer Lifetime Value (LTV)

Customer Lifetime Value or LTV is the value that your user deliver to you throughout the period they are subscribers or users of the product. The objective is to evaluate the financial value of each customer and, thus, direct efforts not only towards the acquisition of new users but also towards the retention of recurring ones. LTV allows for the understanding that not all customers are the same and some represent greater assets for the business. Thus, the investment value to acquire them may even be greater than for others, if this is a strategy chosen by the business. The calculation of the Customer Lifetime Value is – LTV = Retention Rate / 1 + Discount Rate – Retention Rate, where: (1) the Retention Rate refers to how long a customer interacts with specific content; and (2) the Discount Rate is the expected return on investment.

Click-Through Rate (CTR)

The Click-Through Rate represents the number of times users clicked on a certain action in relation to the total number of times that action was proposed. An example of CTR might be the number of clicks on a Google Ads ad compared to the number of times that ad was shown. When the CTR is below expectations, some actions can be used to seek improvements, such as focusing on the language and the target audience, including images that trigger users, improving the buttons (CTAs), and analyzing the conversion funnel to make more precise adjustments. Remember that you need to know the user in order to choose the best option and add greater value.

Conversion Rate (CVR)

The Conversion Rate indicates the performance of your digital product. It measures actions that you want the user to take and, therefore, each one of them will have its own Conversion Rate. For example: if an e-commerce website receives 200 visitors per month and they make 50 purchases, the CVR is 25% (50/200). Now, if in a specific Instagram marketing campaign, 10,000 users are impacted by an ad, and 1,500 actually visit that ad’s landing page, the CVR is 15% (1,500/10,000). Conversion Rate Optimization (CRO) can be achieved by formulating hypotheses for not converting the action and then implementing A/B tests to assess performance.

Churn Rate (CR)

The Cancellation or Abandonment Rate refers to the number of people who stop being frequent users or subscribers of a digital product. Its calculation is made by dividing the number of users who abandoned the product by the number of the product’s active users. It is important to point out that every product will have a Churn Rate; after all, some users will always be leaving your product. The basic condition for success is for the Growth Rate to be higher than the Abandonment Rate and, to that end, some good options are to maintain the good quality of content, deliveries, and customer relationships.

Net Promoter Score (NPS)

We couldn’t wrap up this article without talking about the most famous loyalty metric of them all. Also known as Network Promotion Score, it is used to measure the degree of user satisfaction with the digital product, functionality, or service. Easy to apply, NPS consists of a rating from 0 to 10. With your customers’ data in hand, you can classify them as detracting users, that is, those who have provided ratings from 0 to 6 and are therefore not satisfied with the product; passive users, or those who provided ratings between 7 and 8 and, despite being relatively satisfied, are not brand loyal; and promoting users, or those who provided ratings 9 or 10, are satisfied and encourage other users to join the product. The calculation of the Net Promoter Score is achieved by subtracting the percentage of promoting customers from the percentage of detracting customers. For example, if 85 people provided ratings, 15 detractors (17.64%), 40 neutrals (50%) and 30 promoters (37.5%) – NPS = 37.5% – 17.64% = 19.86%. For reference purposes, an NPS above 75 is considered excellent, 50 to 74 very good, 0 to 49 fair, and below 0 is considered bad.

Options of Tools

Now that you know some frameworks for setting objectives and goals, and you know the main product metrics, it is time to analyze the data. Some tools that can help in this process are Mixpanel, Hotjar, FullStory, and Mouseflow.

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Are you able to validate digital innovation?

Karina Hartmann — Mon, 19 Jul 2021 21:20:53 +0000

These days when entrepreneurship is in fashion and disruption is the new goal of every entrepreneur, I write to ask if you have what it takes to walk down the path of validation.

One of the most challenging phases of digital innovation is the validation phase, where the famous Product-Solution-Fit and then the Product-Market-Fit must be achieved. This is the moment when you take the long-awaited solution to be analyzed by the users and the market.

Resilience and detachment

A famous quote, attributed to Peter Drucker, is that “culture eats strategy for breakfast”. I actually think it is a feast, and one of the diners is the market. By this, I mean that your strategy, on paper, is worthless; it is just a set of hypotheses. Moreover, the more innovative the business, obviously, the more uncertain the chances.

Of course, it makes sense to sketch out strategies, come up with ideas and create business models. However, you need to be fully aware that these constructions are temporary, meant to be modified, improved, and rebuilt. The term to pivot is not just a trendy term; it is a tool to be used. The Lean Startup, by Eric Ries, was not written to decorate bookshelves, but to remind us to test hypotheses.

Then comes the need for detachment: throughout your path in building a digital innovation, it is not possible to keep attached to an initial idea or to a specific business model even after research, tests, and the market show signs that it does not work. Believe me, the journey between idea and Product-Market-Fit is not an easy or short one. It is full of doubts, full of difficult decisions, and even some confusing signs. These fits are not binary; they are not simple questions answered with “yes” or “no”. They are a learning process that requires a lot of interaction with people.

It is necessary to be resilient in order to get through this phase of uncertainty. Knowing that it might not work right away and be prepared to spend months in validation cycles. It is always helpful to remember: the more innovative, the more uncertain. So if you are looking for disruption, be prepared for long periods of experimentation and validation.

Financial Control

An important matter for surviving these long periods is financial control. This means knowing what your cash burn rate is (the speed with which you will invest), and thus optimize the use of money. It doesn’t matter if it comes from bootstrapping, from investors, or from the company that is trying to create a new innovative business. The validation phase is a marathon, not a sprint!

The worst scenario, one that I’ve witnessed several times, is when the entrepreneur doesn’t let go of his initial ideas and doesn’t see the marathon. In these cases, what happens is not wanting to do research, not wanting to carry out experiments, wanting to build “the complete product” right away. However, in this complete product mentality, the entrepreneur is financially organized to run a sprint, not a marathon.

The entrepreneur spends all the time and money he has building a dream and there is nothing left for the validation cycles. It’s like betting all your chips on a single move – the risk of this strategy is very high. For this reason, I believe that the exercise of making financial projections for the validation stage, although full of doubts, is one of the best ways to develop this detachment mentality and convince yourself that it is important to start testing and learning right away.

Ears to hear, eyes to see

I mentioned earlier that the validation phase is a path of uncertainty. It turns out that human beings do not live well with uncertainty. We are programmed to find patterns, and over evolution, we develop cognitive biases. When undertaking, confirmation and anchoring biases come into play, which can prevent us from seeing clearly.

I recently heard from an entrepreneur: my product is wonderful, it’s great, I feel it in my heart. I know that, for years, we’ve been taught that the entrepreneur needs to be very self-confident, needs to believe when no one else does. Well, let me say it is useless to subvert self-confidence into an illusion.

In the validation phase, you need to be careful, have ears to hear and eyes to see to absorb the numbers, listen to feedback, filter out biases, and separate vanity metrics from real indicators. You can’t focus on the number of likes on social media and ignore conversion funnels full of holes.

Integration and knowledge

Focusing on vanity metrics can be the result of a confirmation bias, but it also happens when integration is lacking. In spite of a startup or spin-off being a small organization, there is still the risk of communication not flowing and an integrated strategy not being built.

There is a lot of information being collected in the validation phase. The product is like an airplane full of sensors. There are usage metrics, attribution metrics, funnels, and retention metrics. There are user tests, feedback, interviews. There are perceptions and opinions.

All this information needs to circulate, needs to be known, digested, discussed by the team as a whole. If there is a sales effort, if someone is working in an online presence, if there are people in the operation, if there are people supporting them: everyone needs to be aware that the current phase is one of validation.

It should be clear to the team what we are now testing and what we want to learn from it. It is necessary for the team to be aware that no local efficiency metrics matter at this stage.

In fact, speaking of awareness and information sharing, there is no way to cross this phase without relying on knowledge. A classic fallacy of entrepreneurship is the importance of intuition. Entrepreneurship is not intuition, it is strategy, and a well-informed strategy is better.

The larger the repertoire, the greater the preparation

Thus, to carry out the validation phase, it is important to learn about how to measure, how to evaluate, how to obtain data and feedback, how to interpret them, and what to do with them. This does not mean that you will find ready-made recipes: the validation of a product is in the universe of complex problems, so it is empirical in nature. Nevertheless, even if there is no map ready for your path, there are familiar tools that can help you see your way, and past experiences can help you learn how to read terrain patterns.

The suggestion is to learn about product discovery, product management, product marketing, and all the techniques and tools that these subjects bring. Alternatively, count on the support of specialists, people who already have experience and some tools at their disposal.

Furthermore, learn about innovation and strategy. You can join the startup community in your region, attend lectures by entrepreneurs or leading theorists, read articles and books by those who study innovation and strategy. You won’t get ready-made solutions: you can’t simply copy the experience of others, because in the domain of complexity, a causal relationship is not so simple to be replicated. However, with this study, you can expand your repertoire of strategic options and be more prepared to respond to situations that will arise during validation.

From idea to business

I conclude knowing that this article is not complete, that it does not exhaust the list of concerns and skills needed for the validation phase. Even so, I hope that you, an entrepreneur who has come this far in reading, is resilient enough to cross the validation path, able to enter this phase with the detachment necessary to modify your product and have the financial organization to use the investment strategically in research, experiments, and deliveries.

I also hope that you go through this phase really aware and able to read the signs without getting lost in confirmatory biases. That you can engage the entire team that is already with you in the way of thinking necessary for this phase. And that you rely on existing knowledge and tools to read the terrain and draw your own map for product-market-fit. I even dare to say: either this is all done, or it will be just a waste of time and money with a dose of frustration.

Nonetheless, it is worth remembering that all the effort might be worth it. A well-done validation phase is what takes you from an idea to a business. If you can actually validate a solution and achieve fit, you will be creating the story of a successful, innovative, and perhaps even disruptive business.

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