"Data Monetization" is a term you might have heard a lot lately. But what does it really mean for you and your business? There is gold in your data, but how can you extract it to gain all its benefits without adding resource burdens on your business? We collected the main approaches successful companies are using to give you inspiration and insight into how you can use data you already have to improve efficiencies, create new revenue streams or increase value and hence your wallet share from your current customer base.
Use data to make better decisions
We’re always keeping an eye out for BI and analytics experts to add to our fast growing network of partners and we are thrilled to add a long-standing favorite in the Tableau ecosystem! InterWorks, who holds multiple Tableau Partner Awards, is a full spectrum IT and data consulting firm that leverages their experienced talent and powerful partners to deliver maximum value for their clients. (Original announcement from InterWorks here.) This partnership is focused on enabling consolidated end-to-end data analysis in Tableau.
Whether we’re talking Tableau BI services, data management or infrastructure, InterWorks can deliver everything from quick-strikes (to help get a project going or keep it moving) to longer-term engagements with a focus on enablement and adoption. Their team has a ton of expertise and is also just generally great to work with.
InterWorks will provide professional services to Keboola customers, with the focus on projects using Tableau alongside Keboola Connection, both in North America and in Europe, in collaboration with our respective teams. “We actually first got into Keboola by using it ourselves,” said InterWorks Principal and Data Practice Lead Brian Bickell. “After seeing how easy it was to connect to multiple sources and then integrate that data into Tableau, we knew it had immediate value for our clients.”
What does this mean for Keboola customers?
InterWorks brings world-class Tableau expertise into the Keboola ecosystem. Our clients using Tableau can have a one-stop-shop for professional services, leveraging both platforms to fully utilize their respective strengths. InterWorks will also utilize Keboola Connection as the backbone for their white-gloves offering for a fully managed Tableau crowned BI stack.
Whether working on projects with customers or partners, we both believe that aligning people and philosophy is even more critical than the technology behind it. To that end, we’ve found in InterWorks a kindred spirit, we believe in being ourselves and having fun, while ensuring we deliver the best results for our shared clients. The notion of continuous learning and trying new things was one of the driving factors behind the partnership.
Have a project you want to discuss with InterWorks?
It’s been quite an exciting year for us here at Keboola and the biggest reason for that is our fantastic network of partners and customers -- and of course a huge thanks to our team! In the spirit of the season, we wanted to take a quick stroll down memory lane and give thanks for some of the big things we were able to be a part of and the people that helped us make them happen!
Probably the biggest news from a platform perspective this year came about two years after we first announced support for the “nextt” data warehouse called Amazon Redshift. At the time, it was a huge step in the right direction. We still use Redshift for some of our projects (typically due to data residency or tool choice) but this year we were thrilled to announce a partnership born in the cloud when we officially made the lightning fast and flexible Snowflake the database of choice behind our storage API and the primary option for our transformation engine. Not to get too far into the technical weeds (you can read the full post here,) but it has helped us deliver a ton of value to our clients (better elasticity and scale, huge performance improvement for concurrent data flows, better “raw” performance by our platform, more competitive pricing for our customers and best of all, some great friends!) Since our initial announcement, Snowflake joined us in better supporting our European customers by offering a cloud deployment hosted in the EU (Frankfurt!) We’re very excited to see how this relationship will continue to grow over the next year and beyond!
One of our favorite things to do as a team is participate in field events so we can get out in the data world and learn about the types of projects people work on, challenges they run into, and find out what’s new and exciting. It’s also a great chance for our team to spend some time together as we span the globe - sometimes Slack and Goto Meeting isn’t enough!
SeaTug in May
We had the privilege of teaming up with Slalom Consulting to co-host the Seattle Tableau User Group back in May. Anthony Gould was a gracious host, Frank Blau provided some great perspective on IoT data and of course Keboola’s own Milan Veverka dazzled the crowd with his demonstration focused on NLP and text analysis. Afterwards, we had the chance to grab a few cocktails, chat with some very interesting people and make a lot of new friends. This event spawned quite a few conversations around analytics projects; one of the coolest came from a group of University of Washington students who analyzed the sentiment of popular music using Keboola + Tableau Public (check it out.)
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?
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.
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.
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.”
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.
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.
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.
We’ve recently experienced two fairly large system problems that have affected approximately 35% of our clients.
The first issue took 50 minutes to resolve and the other approximately 10 hours. The root cause in both cases was the way we handled the provisioning of adhoc sandboxes on top of our SnowflakeDB (a few words about "how we started w/ them").
We managed to find a workaround for the first problem, but the second one was out of our hands. All we could do was fill in a support ticket with Snowflake and wait. Our communication channels were flooded with questions from our clients and there was nothing we could do. Pretty close to what you would call a worst-case scenario.! Fire! Panic in Keboola!
My first thoughts were like: “Sh..t! What if we run the whole system on our own infrastructure, we could do something now. We could try to solve the issue and not have to just wait…”
But, we were forced to just wait and rely on Snowflake. This is the account of what happened since:
At the same time as the announcement about default backend in KBC being shifted to Snowflake, I have started working on a new project. The customer pushed us the initial dump of two main tables (10M rows each) and some other small attribute tables.
More than two years after we announced support for Amazon Redshift in Keboola Connection, it’s about the friggin’ time to bring something new to the table. Something that will propel us further along. Voila, welcome Snowflake.
About 10 months ago we presented Snowflake at a meetup hosted at the GoodData office for the first time.
Today, we use Snowflake both behind the Storage API (it is now the standard backend for our data storage) and the Transformations Engine (you can utilize the power of Snowflake for your ETL-type processes). Snowflake’s SQL documentation can be found here.
What on Earth is Snowflake?
It’s a new database, built from scratch to run in the cloud. Something different that when a legacy vendor took an old DB and hosts it for you (MSSQL on Azure, Oracle in Rackspace or PostgreSQL in AWS).
In a recent post, we started scoping our executive level dashboards and reporting project by mapping out who the primary consumers of the data will be, what their top priorities / challenges are, which data we need and what we are trying to measure. It might seem like we are ready to start evaluating vendors and building it out the project, but we still have a few more requirements to gather.
What data can we exclude?
With our initial focus around sales analytics, the secondary data we would want to include (NetProspex, Marketo and ToutApp) all integrates fairly seamlessly with the Salesforce so it won't require as much effort on the data prep side. If we pivot over to our marketing function however, things get a bit murkier. On the low end this could mean a dozen or so data sources. But what about our social channels, Google Ads, etc, as well as various spreadsheets. In more and more instances, particularly for a team managing multiple brands or channels, the number of potential data sources can easily shoot into the dozens.
Although knowing what data we should include is important, what data can we exclude? Unlike the data lake philosophy (Forbes: Why Data Lakes Are Evil,) when we are creating operational level reporting, its important focus on creating value, not to overcomplicating our project with additional data sources that don't actually yield additional value.
Who's going to manage it?
Just as critical to the project as what and how; who’s going to be managing it? What skills do we have out our disposal and how many hours can we allocate for the initial setup as well as ongoing maintenance and change requests? Will this project be managed by IT, our marketing analytics team, or both? Perhaps IT will manage data warehousing and data integration and the analyst will focus on capturing end user requirements and creating the dashboards and reports. Depending on who's involved, the functionality of the tools and the languages used will vary. As mentioned in a recent CMS Wire post Buy and Build Your Way to a Modern Business Analytics Platform, its important to take an analytical inventory of what skills we have as well as what tools and resources we already have we may be able to take advantage of.