Blue Cross Insurance Company

Client needs are on the same plane as Big data. Small data or small data give detailed information. The power of small data lies in the competent combination of two approaches: small data and big data. As players of the same team, best result they bring it together. Let's figure out how to wisely use the benefits of big and small data.

Blue Cross Insurance Company

Imagine that all the data at your disposal were sports commentators. At the same time, big data are play-by-play commentators who give general information, an objective description of the situation - what, where, when; small data is a color commentary - additional, more capacious and targeted facts. Color commentary (additional commentary) contributes to a deeper disclosure of the context.

Metaphor with gameplay Well reveals the essence of big and small data. Big data is a statement of facts as they are, small data shows"tricks" process. Big data is defined by quantitative research, and small data is defined by qualitative research. That is why using only one tool will not give a decent return to marketing research.

Let's see how small data works using the example of the Blue Cross insurance company (life and health insurance). Blue Cross, like many other health insurers, has faced the problem of readmissions—unplanned readmissions to a hospital after primary inpatient care under insurance. Readmission rates are used to assess the quality of inpatient care.

The problem with readmissions is that in most cases they are useless. Returning patients to clinics is more expensive than recovering at home. The company's challenge was to understand which readmissions were necessary and which could be prevented in order to reduce costs. Reducing readmission is one of the main policy items of the insurance company.

To understand what drives patients to be readmitted, the team examined large amounts of data. Blue Cross launched algorithms that looked at patient billing, laboratory readings, prescribed medications, patient height, weight, and family medical histories (play-by-play data). The company also studied the poverty level in each individual patient's area of ​​residence. All data in volume amounted to about 5 Wikipedia volumes.

Big data made it possible to identify high-risk patients. To solve the problem - to reduce the percentage of patients returning - data on high-risk clients was sent for study to health coaches and proper nutrition. The specialists answered specific questions such as: what complicates the patient’s recovery at home? How will the patient’s behavior and habits help him during the recovery period? How can you influence the patient's behavior? This is how the small data approach was used. It turns out thatsmall data fills the gap of big data.

Customer needs are not static, and marketers should always recognize even slight fluctuations in them. This is where a more detailed and meticulous study using Small data helps.

Lego

One of the most big problems today - how to analyze the entire array of big data. We know how to collect data, but we don't know what to do with it. Martin Lindstrom, author of the book« Small data: little things that hide big trends » and Lego brand strategy developer in 2004, believes that if we are talking about studying the desires of our customers, we are talking about small data.

We all love Lego, but the company wasn't always as powerful as it is today. In the early 80s, Lego began to lose ground. New, more modern toys, including Nintendo and video games based on them, have grabbed a serious piece of the market. As time went on and competitors offered more successful and complex games, Lego continued to fall behind.

What was the brand's first tactic? Diversification. Lego has launched theme parks, a clothing line, movies, and even its own video games. This tactic did not bring much results, but Lego remained afloat.

Lego has moved from traditional construction sets to films, games andother products .

With the rapid development of the Internet, digital natives (those born after the 80s) were in constant search entertainment. During this period, brands launched campaigns to capture their attention. Lego has done a number of studies. It turned out that millennials are waiting creative crisis. Every study said that new generations are not ready for the challenges. They are not ready to bother with something that does not bring instant results and instant satisfaction.

What was left for Lego? Less details in the designers, the details themselves large sizes. They increased the details of construction kits, their sales fell. Then Martin Lindstrom was invited to the company with his philosophy of small data.

Old sneakers and inspiration

During one of his marketing studies, Martin Lindstrom and his team visited the home of a German schoolchild. It turned out that in addition to his love for Lego, he was an almost professional skateboarder. Asked to name the most valuable thing in the room, the guy pointed to a pair of worn-out sneakers. It turned out that many hours of training on a skateboard made the shoes ideal for skating. They were old and shabby, nothing special. But thanks to the sneakers he's wearing long hours practiced the exercises, the boy became one of the best skaters.

This small incident proved that millennials and younger generations were not obsessed with the desire for instant results, as big data indicated. The story with the boy showed that his shoes are a kind of symbol of respect for the work he does.

Lego didn't just go back to what made them great. Thanks to a small experiment conducted by Lindstrom, it became clear how to promote the once popular construction sets. The parts of construction sets have not only become smaller, construction sets have become more intricate and complex. It was a bit of a challenge. Today, Lego's sales exceed those of the world's largest toy manufacturer, Mattel, which produces the famous Barbie doll.

Roomba robot vacuum cleaner

Using small data hasn't just worked with toys. Lindstrom has used this idea with other products, from the Roomba robot vacuum cleaner to refrigerator magnets. Small data helps to find seemingly insignificant features of a product and turn them into the main advantages of the brand.

Lindstrom loves the quote« If you want to see how animals live, don't go to the zoo, go down to the jungle» . He calls this process« seeing the subtext» — detailed process collecting information online and offline, observing consumer reactions, even going so far as to invite the client to visit and see how he uses the product.

Very often, the consumer reveals the essence of the product from a completely different angle, recognizes it strengths. Sees product qualities that brand representatives did not notice or considered unimportant. Thanks to this, you can build a new brand image or create a completely new brand.

Lindstrom believes that people don't want to be associated only with what they do. We spend a lot of time at work, but work is not our whole life. Each of us has hobbies and interests. Lindstrom calls it« look through the frames» . Everyone tries to express themselves through hobbies and interests. And this benefits brands. The client's choice is self-expression.The creators of the Roomba robot vacuum cleaner took advantage of this knowledge. They came up with not just a washing machine, but an interactive fun toy with a surface cleaning function. Remember how many videos there were on YouTube with this vacuum cleaner and pets.

In RuNet there is still no clear definition of what small data is, although it would seem that they have been talking about big data for a long time. These two forms of data are similar and dissimilar at the same time. Let's figure out what's what.

Small Data. Definition

Small data is when information about one person is analyzed and conclusions are drawn (respectively, big data is when many people are analyzed and patterns in their behavior are found).

Collecting, processing and interpreting small data does not require many resources: one person can do it. Such data is intended for solving everyday problems, in the case of e-commerce: finding out gender, age, physiological parameters, social status user and other data, you segment users according to recognized criteria and more effectively conduct advertising campaigns and recommend products.

Small data is about everyday tasks: for example, collecting email addresses buyers into your database and sending out newsletters, you also work with small data.

Do retailers need small data?

Small data has a more famous brother - Big Data, a technological trend of the last few years. Retailers need big data: it helps them get an overall picture of the market, see trends, forecast demand or competition, increase sales by understanding customer behavior, etc. There are really many ways to use Big Data - a current example is with recommender systems: they use big data and complex software algorithms to predict a user's needs and interests based on his actions, comparing his behavior pattern with thousands of other similar users. After analyzing the big data, such systems offer him the most relevant products.

But the example above with recommender systems is rather an isolated case in online retail where big data was applied so simply and with such a level of automation. In fact, it turns out that if you just take all this data about users and give it to retail, then only a few will analyze and take it into account when developing advertising campaigns or assortment planning. The reasons are banal: it’s difficult, time-consuming, and if you write software algorithms for analysis, it’s expensive.

It's easier with small data. There are at least three reasons for this:

• They are available.To collect small data, you don’t need scientific methods, a software engine for analytics, building complex hypotheses, and all that stuff. Small data - about known things. Just like big data, small data needs analysis, but it can be carried out using standard business software.

• They are accurate.You are always able to independently update or clarify the data of your clients: whether it is verification of e-mail and phone number on the website or even calling a call center.

• They are functional.Large data sets require appropriate analyst expertise, time, and specialized software. Moreover, there is always a risk of doing wrong conclusions or overanalyze. Small data is easier to process manually and then make strategic decisions based on the findings.

In the book " Big Data Principles » contains key differences small and big data. Let us present them here to finally understand the essence of the issue.

Hopefully the differences have become more obvious. Since our product is directly related to both Big Data and Small Data, let us explain the role of the latter in the work of REES46.

When he comes to the store New user, for the recommendation service it is - Blank sheet. Nothing is known about him, collaborative filtering and other methods of processing big data do not work: after all, we do not know what the user bought, what he watched, etc.

Therefore, REES46, along with large data, uses small data, drawing conclusions based on them and turning them into high-quality product recommendations.

Example 1.The buyer viewed several items in the children's clothing category. The system concludes that the user has children, and looking at the parameters of the viewed clothes, makes a record of what gender the child is and how old he is. Next, suitable children's products are recommended to this user, using Small Data: this way the shortcomings of Big Data are compensated.

Example 2.The customer added Pro Plan dog food to her cart. Based on the volume, the service recommendation makes an assumption about how large the dog breed is, and based on the brand, it assumes that the buyer will be suitable for products from a high quality price segment(food is high quality and expensive). Therefore, recommended products will only display high-quality accessories or toys for large dogs - and this will increase the likelihood of a purchase.

In general, small data is what you need to use when there is no time to process Big Data, computing power or when nothing is known about the user.

The best thing for making decisions here and now.

I haven't been going to the movies to see cartoons very often lately, but I had very good reasons to go to Smallfoot. And I don’t regret it one bit! A wonderful and not at all stupid cartoon, raising not only the traditional theme of good and evil, which, by the way, is quite unusual for a cartoon, but also the theme of the price of peace and happiness, as, in fact, what happiness is.

The cartoon looks unusual from the very beginning, from the very, very first song, which presents us with the Yeti village as a place of absolute happiness, at the same time, this same song literally screams that there is not happiness here, but its surrogate. It is interesting that the village is headed by a hero-priest, who is also a leader, thus, the conditional religious leader here merges with the leader, let’s say, political, which means the presence of absolute power, not challenged or limited by anyone. One person, in essence, can be perceived as a deity, especially since only she is given the right to interpret stones, which are the only ones perceived as laws. Hence the main motive that everyone should be in his place, fulfill his own work, and under no circumstances think about it. This formulation of the question suggests a dystopia, only shown in bright colors children's cartoon.

If the ruler-priest is the embodiment of the highest power in this place of anti-happiness, then the father of the protagonist is the embodiment of the consequences. Although an ideal subject, he is stupid and slow-witted, to which he was literally brought to by strictly following the instructions inscribed on the stones. It is not surprising that he will be on the verge of personal tragedy when his son commits the greatest crime - he begins to think with his own head and look at the world with his own eyes. The tragedy of realizing one's place in a world that was a lie from beginning to end. When, therefore, all life was a lie.

The action develops according to the laws of dystopia, but in a softened version: it has its own underground dissidents, and the main character discovers the truth, which is categorically forbidden to many. An interesting way to pose the question is when the simple values ​​being promoted for a long time things that are quite safe for the regime represented, for example, telling only the truth, turn out to be dangerous for the regime. I would like to note the most striking number in the conversation between the priest and the main character, in which the issue of lying for salvation is brought to the fore, putting our young Yeti before a moral choice, which is difficult for him to make, because he has only just learned to think. The question is not at all childish, since it shows the significance of the priest’s motives, and it is impossible to immediately decide whether he is right.

But much more important question this is the inability to find mutual language. In the cartoon, this is shown literally at first: the yeti Migo appears to the human Percy to be growling and threatening, and the yeti cannot understand a word Percy says. However, these two heroes slowly but surely begin to find a common language, be it the language of gestures or actions. Percy's role may be mostly formal, but his appearance makes Migo think. The interesting thing here is that Percy is not at all ideal, and he is still a “fruit”, and Migo is a pure soul, but Percy turns out to be capable of actions, and, thanks to this, the truth in his person is able to defeat lies in the struggle for Migo’s soul and heart . That is, for the future, because Migo is very young.

So it is Percy, without intending to do so, who forces Migo to open her eyes and understand what exactly is happening. And there is total misunderstanding and fear. People are afraid of yetis, yetis are afraid of people. And, of course, they fight the source of fear. And these two, who are not friends at first, prove to each other that not everyone is bad and cruel. From here interesting look for good and evil: in pure form neither one nor the other exists, and what was traditionally considered good may be a deception, and what is evil may simply be otherness.

The price of happiness in the form of a life of deception and lies is too high, because individuals cease to be such, they become cogs in a huge mechanism, and they cannot be truly happy, because they do not know what it is. Once the sun of knowledge and truth appears, it disperses this darkness, but even if it is difficult, all living beings are still drawn to the light. After all, happiness is only in the light. In essence, Migo in the finale goes into the light himself and leads his people. Towards the light of knowledge, away from destructive fear. He is youth, he is the future, and he is going there, away from the usual primitiveness and even the Middle Ages. He leads people to real happiness.

I would especially like to note the musical design of the film. There are very few musical numbers, but they are very different from those often heard in cartoons. They are bright. At least the usual cute songs. Songs are heard in different styles, there’s even rap, if I’m not mistaken, and the lyrics are quite bright and interesting. The numbers fit well into the cartoon, do not get out of the plot, and do not seem inserted simply for their own sake.

I can’t help but mention the dubbing: finally, both the speech and the vocals of the characters are voiced by the same actors! It sounds much more natural. And finally everyone is recognizable. Viktor Dobronravov’s voice suits Migo very well; the actor definitely managed to convey the hero’s youthful adventurism and conviction. He was able to convey all the shades and intonations so that the Russian audience would believe the hero. Andrei Birin incredibly successfully felt some of the slyness, a little hooliganism of his Percy, he was able to revive, “color” the character of a slightly passable character, and all thanks to precisely chosen intonations and the correct presentation. Gosha Kutsenko voiced his leader-priest in the best possible way: this voice has the wise fatigue of a universal mentor, and a wonderful rap number - it’s impossible not to note it. Natalia Bystrova voiced, in essence, a typical heroine, albeit a combative one, and the actress’s clear voice perfectly complemented Michi’s bright image.

“Smallfoot” is very good to watch: he is kind and positive, and, importantly, he is not stupid, he tries to talk to children like adults. Raises difficult questions. It is bright, with an interesting plot and a wonderful musical part. What more could you want? A wonderful cartoon.