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In 2017, focusing on children's logical thinkingOnline Education Brand Spark ThinkingFormally established, relying on the form of small class live class and real interactive AI class, Spark Thinking combines the teacher's inspirational guidance with animation, games, fun teaching aids and other carriers to guide the development of children's logical reasoning and problem solving skills at all levels.
Up to now, the cumulative number of students of Spark Thinking has exceeded 700,000, making it a leading company in the domestic online education industry.
Among them, "digital intelligence" is one of the pedestals for the rapid growth of Spark Thinking.
To a certain extent, online education itself is a data-native industry, just that most online education enterprises alone cannot do to give full play to the potential of data value. Spark Thinking has realized this and made scientific choices to finally realize the successful release of data potential and ignite business growth.
So, where exactly is Spark Thinking's digital upgrade burst?
01 Universal Data Consumption Ignites All People to See and Use Data
● The core product involved in this scenario:DataWind
/ Core presentation
1. Why：The core fallout of digital operations is to have a better level of data consumption within the organization. Whether it's the data team or the business operations team, but also the functional teams within the organization, spark thinking past the state of BI system usage doesn't lead to more pervasive data consumption for the organization.
In the past, SparkThink had built a BI system, and the highest monthly activity of the system was around 300 people at that time. The original self-built data system because of the high threshold of use, the use of poor experience, most of the time only data analysts, product development team two types of people will be frequently used, business operations team employees to use it need to master certain code skills.
2. Now：Volcano Engine DataWind platform DataWind around the volcano thinking to achieve business self-service analysis on the vision, through access to multiple sources of heterogeneous data, say goodbye to the original self-research BI system SQL capability requirements, so that the company's business personnel, are able to drag and drop the interface, data query and charting, the formation of different business themes dashboard.Enable business people to see the data and consume it.
/ Customer site
1. 2-fold increase in monthly activity of data systems
With features such as visualization and intelligent analytics provided by the volcano engine's digital intelligence platform DataWind, even theBusiness operations employees who don't know code language at allYou can also see and download the data you need directly from the data dashboard, and make the next step in fine-tuning your operational actions based on that data.
For example, Spark Thinking adds additional management intervention processes outside of the platform process in pursuit of a better learner experience and higher completion rates.
In the past, this would have required the middle office to first download an Excel list sheet from the BI system, and then team members would have needed to break down the list from region to team to sub-team and frontline managers, level by level - a lot of staff time was thus consumed in breaking down the list and distributing tasks.
But through DataWind.Frontline business managers themselves can see the details of their team's corresponding students' classes and absences directly from the data board.The instructors were then promptly asked to remind the participants to make up the missing lessons and get feedback on the data.
On the one hand, team members don't need to stare at Excel sheets and break them down level by level; on the other hand, frontline teaching managers can simplify their work and get feedback on the effectiveness of the implementation from the data, so that they can devote more time to teaching and management.
Thanks to the easy-to-use product features, more and more employees within Spark Thinking are becoming data consumers:The data shows that the monthly activity of the data system is now around 800 people, which is two times compared to before;
And in last year's third-quarter system experience NPS (Net Promoter Score, a statistical measure of user word-of-mouth) for internal employees.The value also rose to 0.7 from 0.2 previously.
2. "Academic health" increased by 5 percentage points
Through DataWind's visualization Kanban capabilities, Spark Thinking can take multi-dimensional academic data under the Academic Healthiness IndicatorsPresented directly to instructional administratorsIn this way, the business teams will be able to look at one piece of data to see if their programs are really driving improvements in academic health, and the middle and senior management teams will be able to have the sub-teams learn from each other's successes to promote the overall quality of teaching and learning.
It is also because of the low-threshold nature of the Volcano Engine Numerical Intelligence platform product that lowers the threshold of data use within Spark Thinking, where the head of the middle and senior management team can gain timely insight into the teaching process and replicate excellent examples, and teaching managers can make timely adjustments to course content and teaching strategies in response to the data-...With the application of data-guided decision-making in dual roles, Spark Thinking has seen a 5-point increase in learning health, while also driving an increase in learner retention.
DataWind Demonstrates Growing Trends in Academic Fitness
02 Efficient Business Decision Making Igniting the Science of Business Strategy
● The core product involved in this scenario:DataFinder+DataTester
/ Core presentation
1. Why：When exploring new business, if you follow the traditional AB experiment method of spark thinking you need to wait for another month or even a few months of traffic settling period, if you change to other testing methods, you are limited by the complex process and involve more resources.
2. Now：DataTester is able to perform A/B experiments with smaller samples, theReduce the traditional A/B Test feedback cycle from monthly to weekly.With DataFinder and DataTester, Spark Thinking's marketing team can monitor the progress of experimental data and analyze the differences in user behavior paths on their own.
/ Customer site
1. Increase the success rate of new business user registration experiments by 30 per cent
The team in charge of the new business tries to use DataFinder and DataTester to carry out full-process self-service operation on the business homepage. Even if the traffic is lower than that required by regular AB experiments, it is still possible to open experiments through DataTester and track the experimental process and result data in real time;
Meanwhile.DataFinder also helps teams gain insight into the path of user activity in new business scenarios, theAnd further analysis can be done. In less than a month, Spark Thinking's new business has produced experimental results, with superior registration models that can increase success rates by almost 30%.
Everyone can consume data, everything can be data-driven, theIt is becoming a daily routine under the spark thinking digital intelligence upgrade, which also coincides with the new model of enterprise digital intelligence upgrade launched by the volcano engine.
In the opinion of Junying Zhang, vice president of technology at Spark Thinking, theThe Data Flywheel provides a new way of looking at business and is supported by a large number of digital intelligence products that enable organizations to predict the future based on the Data Flywheel through data.
This is particularly important for enterprise management that needs to rely on data to make scientific decisions. Currently in Spark Thinking, both business front-line management and enterprise core management have become one of the main groups of data consumers.
He gave a visual example: for example, wanting toprojecting the company's business volume in 3 or 5 years.One logic is to make some assumptions about each process and each link from front to back according to the company's business flow, but the final calculation in this way will produce a big error with reality;
Another logic is to look at the business as a whole and turn it into a pool model with growth and churn, and the assumptions made on the basis of this model can be more accurate.
The key to the latter logic is the need to turn horizontal enterprise business processes into a vertical holistic model, a process that requires large amounts of data to be analyzed from multiple perspectives.
With the help of a data flywheel, it is easy for management to see the business from all angles, especially with the aid of a large number of digital intelligence products, such as data analytics calculations, which can help management better predict the future of the business through data.
At this stage, through the practice of spark thinkingSame Data Flywheel SolutionAlready online.