Keboola’s Solutions for Agencies

We would like to show you how some of our clients redefined their businesses by routinely using data in their daily activities. Despite the fact that each company’s situation is different, we hope to give you some ideas to explore in your own business.

If you work in a service agency, as a customer care manager or in similar type positions, you are all about efficiency. Any idle time spent on non-revenue generating activities means wasted time and manpower, and more importantly, a net loss for your organization.

To ensure optimal operation, you may be asking yourself questions like this:

  • Is your team correctly prioritizing clients with a higher profit margin?

  • How are individual team members performing compared to each other?

  • Are team members doing the work they are best suited for?

Earthworms

Sometimes the simplest graphs show the most relevant information. The graph that you see below (generally known as "bullet chart") has been coined the “earthworm” by our clients. Provided by one of our clients, this particular graph eloquently shows agent performance overall, as well as in comparison to the team average.

As a manager, imagine having one of these for each of your agents. In a mere seconds you can distinguish your top vs. poor performers and take the actions needed to enhance or improve their behavior.

Customer Care

Diving deeper into individual performance, you can then examine why each agent is performing the way they are. After you take a look at the next client example, you will see that this series of earthworms track agent performance in different areas.

Keboola’s Marketing Solutions

Even though we understand that every company and each department within it have very different BI needs, we also believe in sharing inspiration from our clients about how they make relevant business decisions using data in their daily routines. You might find this helpful in shaping your own solution.

When planning a new product launch and deciding where to spend your marketing budget, you probably have questions regarding the impact of your campaign:

  • How long will it take to turn marketing leads into faithful customers?

  • Did I target the correct customer group?

  • Do my potential customers respond to the advertisement as expected?

  • What is the return of investment for my campaign based on different target groups and products?

Check out similar questions our clients have asked. Combine them with an analytical mindset, and create the reports your company needs to invest in better marketing decisions, and to generate a higher return on investment.

Roman Novacek from Gorilla Mobile says: “When looking at our marketing model, everything seemed to be going according to plan. But when we looked deeper into what we thought were well-performing campaigns, we found out that while some ads and channels were performing extraordinarily well, others were draining the overall average leading to mediocre results.”


sales funnel


McPen: Built and Run on Data

McPen is a European chain distributor of stationery goods. They are one of the first small to mid-sized retailers who use a data-driven approach to business and enable equal access to data to all of their employees.

Initial situation

Embarking on their data-driven business journey, McPen realized that to excel in the stationery goods space, they would need to create a competitive advantage with a unique operational management system. In order to identify retail solutions specific to their business, they wanted to combine many previously unconnected data sources, and upgrade and speed up their reporting process.

Where Keboola came in

Assisted by the Ascoria team, our partner, McPen’s CEO Milan Petr configured the new system from scratch and without the help of a single developer. McPen began to pull data from sources like their POS, Frames and other retail sources, allowing everybody in the company to use this compiled and easily accessible data to find solutions to their real retail problems.


Focusing on lean operations and adding new features, Milan created a system that benefitted the entire organization. He knew that to effectively manage shifts in business, he had to involve every part of the organization in making decisions based on data. Leading by example, he developed and studied the system in detail to understand its impact on daily operations. He then provided access and support directly to the people on the floor to empower them to make necessary strategic decisions and improve their daily results.

metrics-2


Surprising benefits and results

Examined data showed that in order to maximize profitability, McPen needed to upsell customers. And while their biggest income comes from customers who spend between 200 and 500 CZK (around 8 to 20 USD), it is the 42% of all McPen customers spending up to 50 CZK (around 2 USD) who have the biggest potential for the upsell.

The value of text (data) and Geneea NLP app

Just last week, a client let out a sigh: “We have all this text data (mostly customer reviews) and we know there is tremendous value in that set but outside from reading it all and manually sorting through it, what can we do with it?”

With text becoming a bigger and bigger chunk of a company’s data intake, we hear those questions more and more often. A few years ago, the “number of followers” was about the only metric people would get from their Twitter accounts. Today, we want (and can) know much more; What are people talking about? How do we escalate their complaints? What about the topics trending across data sources and platforms? Those are just some examples of questions we’re asking of NLP (Natural Language Processing) applications at our disposal.

Besides the more obvious social media stuff, there are many areas where text analytics can play an extremely valuable role. Areas like customer support (think of all the ticket descriptions and comments), surveys (most have open-ended questions and their answers often contain the most valuable insights), e-mail marketing (whether it is analyzing outbound campaigns and using text analytics to better understand what works and what doesn’t, or compiling inbound e-mails) and lead-gen (what do people mention when reaching out to you) to name a few. From time to time we even come across more obscure requests like text descriptions of deals made in the past that need critical information extracted (for example contract expiration dates) or comparisons of bodies of text to determine “likeness” (when comparing things like product or job descriptions).

The Beginner’s Guide To Keboola III: We ♥ Your Third Party Data Sources

You’re certainly using them, you probably like them, and perhaps they even help you save some money. However, you’ll find the real treasure of third party data sources the moment you interconnect them and find the answers to your business questions.

In this edition of the Beginner’s Guide you’ll find out how to use data from external services and databases to better understand your data. You will also begin to recognize the importance of getting to know your data (actually it’s time to become best friends), and how to ask the right questions to get the right results (or buckle up for one bumpy ride!).

What data sources does Keboola use?

The short answer…...lots. At Keboola, we are able to connect to most modern systems. We simply need to find the API and it’s ready, set, go.  We like to think of APIs as magical translators that allow programs to exchange data and thus make it more meaningful to you.

These are the 9 nominees for “most used source in a Keboola project” (in no particular order):

Although these are the most common, the potential for new sources is limitless (and that is why we love our dev team).

If it is readable, we can use any kind of data.

Along with service and applications connections via API, you can send us your data in almost any format. We are able to read data in everything from CSV to JSON to unstructured text in a notepad.

We can even go beyond text data and bring in pictures (bless the magic of OCR) if you so desire. The most important thing to remember when bringing data in is that it needs to be readable.

Once we have established the readability of your data we can start building out your project. Our process is generally top secret but usually involves locking ourselves in the office, utilizing only food delivery trucks for survival. We think through the logics of connection, carry out tests, and write documentation. We are then ready to upload your data and start building reports for your viewing pleasure.

Sounds great, except I have no idea where to start and what to do!

Don’t panic. Data can seem overwhelming but it is all about asking a few simple questions and then doing a few simple things.

Start by asking yourself some questions like:

  • What exactly do you want to assess?
  • How can data help you with that?
  • What indicators do you need to watch?
  • What information is missing from the tools you already have?

Next gather the data. 

For external sources begin investigating how information is communicated, the magical translators known as APIs are a great place to start. For internal sources just keep doing what you are doing and update the information you already have. If you haven’t started yet, think of ways to capture that internal information and initiate the process.

By doing some strategic thinking and then organizing your data you are well on your way to creating the right results. This process also helps to explain why more expensive data services are not necessarily better than those that are free. What matters most is the relevance of your data to answering your business questions.

It’s sort of like buying an s-class Mercedes for a ride through the rough and rocky Rubicon Trail. Arguably Mercedes makes one heck of a car, but if you don’t ask where you are going it might be a rather unpleasant ride for you and the car. That’s why it is important to ask questions first and then collect, collect, collect until you are able to cruise through to the right results.

We have to drive off into the sunset for now, but stayed tuned as we builds on this idea in our next article featuring an interview with Tomáš from Czech Keboola.

The Beginner’s Guide To Keboola II: How It Works

You already know that Keboola can process your data in such a way that it makes sense and that it is of value to you. This time we shall go a little deeper and show you how it is done in practice.

Let’s say you're the owner of a chain of coffee shops. You wish to expand your business and at the same time you would like to figure out where you are losing money. You have lots of data from your POS system and of course your accounting software.

This is where Keboola steps in.
  • Together you will identify and gather your KPIs - the parameters you want to monitor. Maybe the average spending by cafe and waiter. Or customer loyalty. Or anything else.
  • Together you can come up with reports you wish to follow. How they should look like and what they should compare.
  • You can start looking forward to a return on your investment.

Now it is time for the "IT stuff"

We will create for your data a model with a clear structure in the Keboola Connection tool. It is thanks to this model that later the whole system will tread quickly, flexibly and accurately. Using the model we will be able to find relationships between the data.

But the model wants to eat – the model wants to be fed data. Which, will come mostly from these four main sources:

  1. If you run your own database, we will connect to it remotely and process all the necessary data. 
  2. If your data is scattered in multiple systems or locations, we will tell you exactly how to connect the dots with our interface. 
  3. Do you wish to relate your data from cafés sales with your website traffic from Google Analytics data? Or with population using open data from your city hall in each city and neighbourhood? We can do it for you! 
  4. Historical data is not a problem either. (Yeah, we're talking about the 10 -year-old Excel sheet with sales data). All you have to do is keep its structure. 

A short wait for the first report

Once we have fed the model with data, we will send the processed data into an application called GoodData. After which, you almost immediately gain access to your reports. Rest assured that the first contact will feel a bit like magic.

Once you’ve had your first dose of satisfaction, we guarantee you that you will want more: "I do not want this report and I want that report to take weather into account." Ok. Post your requirements and wait for two months for a couple of days and then you are looking at your new reports.

Or even better - access our know-how in Keboola Academy to learn how to work the system and then you will be able to modify the reports yourself. After that no one will ever be able to tear you apart from your data. 

A boss with GoodData, who is lounging on a beach half a world away, knows more than any boss present at work without it.

Now, if you wish you can sit under a beach umbrella in Honolulu with a tablet and every five minutes you can check just how much money you are making. 

You will notice that the people who were served by Olivier never came back to your cafe.

You will see that customers in Vancouver are spending roughly twice as much as customers in Quebec, as you just launched an advertising campaign in there.

You will observe that when it rains your sales of pour over coffee rise sharply – unless the manager forgets to stock up on the filters.

You will clearly see how the purchasing behaviour of your customers changes in time, so you will spot new trends early to take the full advantage.

As you sip your Mai Tai slowly, you’ll then start to write your first email: "Mary, please order extra thin filters for our coffee machines and also tall glasses for Vancouver. It seems like there's a new fad..."

Seznam's Return on BI, Part Two

No one has been fired because of the data yet – Michal Buzek reveals the backstage of Seznam’s Business Intelligence

When we last spoke with Michal Buzek, we uncovered that Seznam’s investment in business intelligence paid itself off more than 10 times in only three months. However, we wanted to dig deeper into the specific changes GoodData made in the work of business teams, how it affects the running of their company and how Seznam will leverage data to evolve.

Does GoodData give you any answers out of scope of the regular reports?

What exactly do you mean by regular reports? The fact is our salesmen know their clients much better thanks to GoodData and this, in my opinion, is priceless. Today we know that our client invests tens of thousands with us, but at the same time spends millions on billboards. We therefore work with the seasonality, and we are approaching people according to the branches of their business. We can also analyze the portfolios of businessmen and business teams, and find clients who we can provide with better care. We were able to do all this before (and we did) but it’s incomparably easier and quicker today with the use of GoodData.

I think the key is not one all-encompassing report that opens our eyes – it is having a set of practical reports that are always on hand and are used to help in our everyday work.

Are the business people easily getting used to it?

A few times in Seznam I have heard that a business person is supposed to do business - not rummage in tables. That is why we debugged the reports and made sure the graphs are clear and understandable at first glance. Thanks to that, GoodData became an everyday tool for a business person, a tool that they use before every meeting with a client. This allows them to find out the client’s media strategy, advertising development, customs, and many other types of data before the meeting even begins.

Has analytics ever helped those business people that you thought wouldn’t have been as receptive to the technology?

Some have discovered GoodData already, others still have ways to go. But this year I have noticed a greater hunger for data among the business people. From some of them, I  absolutely haven‘t expected that. It‘s a pleasure to see that GoodData is not just a tool for the top and senior management. All employees can profit from using this tool and gain useful information from GoodData.

Have you let anyone go based on the data?

Not yet, or not that I know of.  But I must say, the business projects in GoodData allow the managers to control their people much more effectively.

Can you be more specific?

The manager is able to see the content of contracted advertisements and the number of visits of every single client. If for example, the client contracted orders of 50k and the business people came to visit 15 times, it tells you something is probably wrong. Conversely, it’s also a mistake when you see a client with advertisement costs of over 2 million and in the history of communication you can only see one record. Either the business person is extremely effective or he doesn‘t care about completing the records from the meetings. 

Do the managers use this information or are they just aware of it?

They use it. Based on detailed statistics they are able to talk to their people in a much more specific way. You can see immediately where a business person is wasting their time and what they should be focusing on instead. Of course you can’t exaggerate these statistics, but I hear a lot of positive feedback from the managers.

Has data analytics changed how Seznam functions?

Most of the people in our company know that the only correct and important numbers are found in GoodData. The top management gather the information necessary to manage the whole firm, the Product Managers follow KPIs and task fulfillment, the Controller sees the expenses and incomes, the Business Managers follow the results of their teams and clients, and the PR department see the statistics from social networks etc.

What about people from other departments? Do they contact you with report demands?

Yes, they do. It’s great that the grapevine works in Seznam. For example, last month the guys from Sklik came to me, as well as the Manager of Mobile Advertisement, and  the Planner of Media Space. They saw some useful reports that other people had and wanted to make their own. They saw that it could actually help them with their work.

How many people use GoodData at your company?

About 75, with 50 of those working in sales. Some managers even use GoodData to make XLS or PDF documents of which they share with others; so in the end there are many more people working with GoodData.

Have the outputs from GoodData found their way to your office meetings?

In the meetings of top management, reports from GoodData have become a standard for the past couple years. We have used these reports to review expenses, incomes, the fulfillment of indicators compared to plan along with other factors. At the meetings of business teams, they mostly discuss reports with advertisement monitoring, the history of communication, and the advertisement outputs in concrete advertisement products. Also, people from services, sales, and marketing regularly meet and watch their KPIs in Seznam.

What do you see as the biggest profit from GoodData/Keboola solutions?

I have mentioned many profits already, so I’ll share with you some of the other added benefits. The greatest pleasure for me personally, is when I see the people in company actually using GoodData and Keboola. I get to see them absolutely excited about the dashboards that we‘ve made for them, even though we are just showing them the data we have always had in Seznam. Before it just wasn’t so easily accessible and now it is all in one place. There also wasn’t the possibility of examining information in the detail there is now.

Is there any report that you prefer?

I think the strength is in its simplicity. The business people prefer that the tables are loaded with useful information. For example, rows show information on clients, columns show information of their price list expenses at Seznam and outside Seznam. The business people are thrilled when they’re able to find the place where our client advertised and exactly what they promoted all in one simple click.

I personally like the tab with two flow charts. For instance, on the left this tab shows the extent of a client‘s investments into advertising by their price list from the database of advertisement monitoring. The one on the right one shows the extent in real prices from the sales system of Seznam. 

You can therefore see things like this client advertised heavily in 2013 – but not at Seznam. Thanks to the data that fact was uncovered and our business people managed to put Seznam back in the game in October.

So what’s next? Have you got any ideas where to go next with this whole thing?

My goal is to help Seznam build extremely efficient business teams. As our sales director once said – “we should be able to send our business people to the right clients, in the right time, and with the right offer”.

How can data help that goal in your opinion?

I want the business people to see themselves in GoodData. Based on the data I want them to see what clients they should approach first. Expanding by more data sources would also help with this, as well as getting more detailed client segmentation. What’s important with all this is education. Right now we are preparing a workshop for business managers, so they can get the most information from GoodData for their work.

Do you think you‘d manage to work without GoodData and Keboola Connection today?

Well if you offered me a tool equipped at least as well as GoodData, then I would.  But I’m a realist. If there was anything better in the market, I would be aware of it. But certainly, I wouldn’t want to return to the Excel and Access times.

Do you feel you are more beneficial to your company thanks to data analytics?

That’s a very difficult question. I try to be that way. But the benefit doesn’t depend entirely on me or the guys who work with GoodData. What’s important is the support of the data from the sales department and from the whole company. In other words – it’s important how data is acquired and used in practice. I think that we have been able to convince more people in Seznam about the value of data. And hopefully, thats how the influence of the analytics department grows.

You’re not getting out of it so easily – has your value on the labour market grown?

When it’s needed, I’ll put it in my CV. I have been here since the very beginning of implementing GoodData into Seznam. I’m able to arrange datasets and build a data model in Keboola Connection. I’m no star, but I have gathered some experience and even if I didn’t need it anymore, the last two years with GoodData and Keboola were really fun for me.

Would you go into the whole thing again?

Definitely. If I ever finish at Seznam and some other company wants me to go through their data, I’ll totally go across Karlín in Prague.

Seznam's Return on BI, Part One

Seznam's Return on BI, Part One

The investment in Business Intelligence returned 10 times in three months, says Michal Buzek, the chief analyst of Seznam

Czech’s biggest web portal, Seznam.cz, has not only built a search engine to rival Google, but has also founded an empire of prospering services. From an email platform to a growing network of contextual advertisements (Sklik), Seznam has excelled at building a portfolio of complementary business ventures.

So how does this giant with thousands of employees, manage and understand the infinite amounts of data at their disposal? One word, GoodData. We sat down with Seznam’s Head Analyst, Michal Buzek, to dig deeper into this trade secret. The following two-part interview will uncover how an investment in their data has payed off by more than 5 million in profit.

How did it all start?

Some time around 2009, a decision was made to implement a Business Intelligence tool and an open competition took place. The former CEO of Seznam, Pavel Zima (now a deputy chairman of the managing board), invited GoodData to bid. At the time, I was part of the team that compared offers and provided recommendations to management. We met with Zdeněk Svoboda (co-founder of Good Data) a few times and he showed us GoodData’s capabilities using a sample of our business data from Sauto.cz. Compared to on-premise licensed BI tools, GoodData was extremely simple and quick; and on top of that, Mr. Svoboda was very smooth and natural in selling it to us. 

Why exactly did you search for Business Intelligence tool?

We needed to escape from Excel – when everybody was bringing their own report to a conference, and the quality of the data was unsteady. What’s more, we had about four different business systems at that time. Long story short, we were looking for an integrated reporting tool that would allow us to get all the data we needed under one unified dashboard. 

And how did you encounter Keboola?

We’d been using GoodData for about two years, but didn’t launch any big actions in that area. From time to time we asked for a modification of the data model, but it wasn’t until our PR department found out that GoodData had the capabilities to interact with social networks that we were introduced to Keboola. We were told that they had developed the best connectors of Facebook and Twitter data for integration with GoodData.  

What was your first impression?

Finally someone who resembles the types of people you can find here at Seznam. No suits.

So it all started with the project of getting the data from social networks?

Yes, but I had actually wanted to try something new in GoodData even before that. I wanted to expand the data models and play with other views on our data to see whether I’ll get someone else excited as well. I also wanted to accelerate additions of new items without the need to consult with GoodData each time.

Meanwhile, Keboola came and showed me some ways to improve the Dashboard in GoodData and also had their own tool, Keboola Connection. I won’t lie – I also read Tomáš Čupr’s (well-known Czech businessman, the founder of the most successful variation of Groupon – Slevomat.cz) post about the way they changed his life.  

So what happened next?

In March 2013 we started building a new project for the sales department. I wanted to give the salesmen a fundamental reason to use GoodData. We’ve been buying market research data for some years by that time – specifically looking at expenditures on big-format advertisement - but we haven’t had a chance yet to maximize its potential.

Recently, we connected this third-party data with our business system. In doing so, the knowledge of our current and potential clientbase shifted about five levels ahead. We gave our salesmen a simple tool to trend what types of advertising is purchased, how often and where from, so that they have a better understanding of the buying behaviour of our clients. This took us not one, but five levels beyond what we had before. 

Was it difficult to learn how to work with Keboola Connection?

No, there wasn’t much extra to learn. The data transformations in Keboola Connection are written in SQL, which already has been used by our team. I personally got the hang of it after a few weeks. My favourite toy is Sandbox, a “training environment” in which I can send input tables and play with questions long enough to get the appropriate result. 

What have you already managed to create?

The sales department of Seznam is quite big and the teams are diverse, so the demands for the statistics are varying. People from Sklik need one kind of report, the team specializing in serving large clients needs another. This is why we are continuously developing the project and we cannot just set things up once to be done with it. That being said, I have yet to see an inquiry that we couldn’t solve with Keboola Connection’s help. 

And what specific projects have you launched?

In GoodData we have taken on several projects, beginning with the social networks and ending with the buying behavior of clients. We divide clients according to their industries, we watch their seasonality according to the attendence of categories on Firmy.cz and we try to approach them proactively based on this gained insight. The salesman picks a category on his dashboard and is then able to see listed clients, their solvency and their spendings outside Seznam. From this, he knows exactly who and when to call. 

How is the sales team responding to Keboola Connection and GoodData?

The sales department has their people 100 % under control thanks to Keboola and GoodData, so their response is of course very positive. When you hear a sales manager with more than eight years of experience saying that he cannot imagine his work without GoodData anymore, it’s certainly something you like to hear. 

Does it pay off financially?

After three months of the project running, I could easily see the results (in dollars) through the business managers’ performance - of which we knew certainly was earned with thanks to information from GoodData. I can’t talk in exact numbers, but the investment into the database and BI consulting was in the hundreds of thousands range, and was payed off by more than 5 million in profit. 

So it does really pay off?

Sure it does. Not only does GoodData help us to generate more money, but also to find the areas where we can keep from losing it. A businessman can only use his time and energy where it’s worthy. Decisions are not driven by gut feeling anymore, they are based on hard data. We see costs drilled down to the tiniest of details. We can find the causes of growth and we are able to see what and how it exactly impacts our profit.

Seznam's Return on BI, Part Two

The Beginner’s Guide To Keboola

"The whole thing is a bit complicated…" started Vojta, one of Keboola’s consultants, over an English breakfast in the coffee shop with the best coffee in Prague. He was right. It was complicated. But a few hours (and a pint of coffee) I got pretty good idea what was going on. Here, I will try to relay it to you.

Intro: Companies today often have enough data to get completely lost in it and it is unfathomable to put it into context and extract any useful meaning. Even if they can, there are high costs associated with time and money.

Finding the gold in the data

Keboola does something called data ETL (Extract, Transform, Load). It sounds (just like many other fancy terms from this field) more complicated than it is.

Keboola helps you:

  1. Identify, locate and pull together all data relevant to your business from both your own and third-party sources. Anything from accounting and ERP systems to some related open-data initiatives of the government to comments on your Facebook pages. This is the Extract stage.
  2. They manage the whole load, organize it into a structure in which one can meaningfully work with it. That’s Transform.
  3. Then the data is pushed into the system or application selected for the final consumption - Load.

The toolset that Keboola uses to perform (amongst other things) the ETL tasks, is their own Keboola Connection.

The platform that Keboola uses for the analytics and producing all of those wondrous charts and dashboards is GoodData.

So what is it all good for?

You’ve got data. Lots of it.

To give it meaning, the data needs to be pre-processed, the pieces put in order and with the right context, so that GoodData will give you the results you need. That is what Keboola is for:

  • Helping you to find meaning in your data.
  • Continuously processes your data using Keboola Connection
  • Sets up GoodData so you can find the answers you need. Answers to questions like "how much revenue did we get from customers brought to us by the expensive marketing campaign from last fall?” or “what impact does weather have on our sales people’s performance?” Or whatever else comes to mind.

Keboola can do all of that pretty fast and practically without limitations. But that’s my topic for the next time.

If anything here doesn’t make sense to you, please ask! I’ll reply and explain better in the article.

Behold. The Official Keboola Blog has started

Hi! I am Martin, official Keboola Data Rookie, here to share the first post of our new blog!

My goal is to explain what it is we actually do here at Keboola… which can be pretty hard to sum up in one sentence. Every side of Keboola tells a different story, so each month we’ll give you insight into our business from a different perspective. With every post I hope to tell you something new and exciting, but if you’re still left with burning questions please let me know so I can answer them! 

Here’s a taste of what you can expect to see:

  • Keboola Basics. Or kindergarden for data analysts - as simple as what Keboola does, for whom and how. (Successfully tested on my grandmother)
  • Data for Business. We know you want to see numbers, but we also want to give you a comprehensive overview of how and what Keboola does to help companies earn big money through Big Data. We’ll share these stories through interviews, case studies, and our cultivated best practices.
  • Nerd Zone. For the tech savvy and future innovators, this is the space where analysts can embrace their inner geeks. Look forward to detailed articles full of pure know-how.
  • From Keboola With Love. With offices in two very (culturally) different time zones, get a behind the scenes look at what happens on the other side of the screen.

From one data enthusiast to another, thanks for taking the time to hear what I have to say. Stay tuned for our next post where we sit down with Michal Buzek - head of the analytical department at Seznam.cz (a respectable Czech rival of Google) – and find out the results of his project with Keboola.