Akbank is one of the largest banks in Turkey reporting a net profit of TL 4,854 million (~ USD 1,387M) and assets of TL 295 billion (~ USD 84B) at the end of 2016. The bank’s consolidated capital adequacy ratio of 14.2 percent, calculated according to Basel III standards, is among the highest in the sector. In 2016, Akbank was voted as the “Bank of the Year in Turkey” by The Banker, deemed the “Best Bank in Turkey” by Global Finance and the “Best Bank in Central and Eastern Europe” by Euromoney. The company has also been named “Most Valuable Banking Brand” in Turkey for the fifth consecutive year in the international brand valuation company Brand Finance’s survey.
In the highly volatile global environment in 2016, the Turkish economy continued to grow strongly led by private consumption and investment spending. This presents tremendous opportunity for Akbank to grow its business, as well inviting furious competition for banking services for consumers, private clients, and corporate customers.
To execute on its pledge of sustainable return on equity of at least 15-17 percent, the customer-facing side of Akbank faced four key challenges:
• Become a leader in Turkish banking sector in terms of customer experience and satisfaction, along with value to the customer
• Build stronger relationships with customers to increase retention and reduce churn
• Grow their customer base in both the consumer and corporate markets
• Increase the wallet-share and lifetime value of existing customers
Analytic and Data Challenges
At the heart of Akbank’s strategy was to increase the agility of their marketing and sales campaigns to provide the proper offers and messages at the right time to prospective new clients and existing customers.
With 90 different marketing campaigns running simultaneously, Akbank’s existing
architecture posed many challenges to achieve their desired agility:
• Siloed campaign data stored in over 10 different data sources made it difficult to get a consolidated view of marketing campaign results
• Long, complex analytic processing cycles where individual queries could take
up to 24 hours, and the entire results generation process would take 4 to 5 days
• Manual SQL-based reporting processes which were constantly updated,
creating version control headaches and errors that were only identified after
measurements were taken
Because of these complexities, Akbank could only measure the performance of
their marketing campaigns monthly, and only then make adjustments to improve
results. This certainly was not agile, and according to Attila Bayrak, Chief Analytics Officer at Akbank:
“Our inability to see results while campaigns were running prevented us from
making adjustments as needed. We needed a platform that would allow us to
change the strategy while in the game, not after it is over.”
The Datameer Solution
To deliver the desired agility, Akbank required a big data
platform that would consolidate their disparate data sources,
speed the time to insight, and eliminate errors. Datameer
• Easy integration — Datameer’s data ingestion and blending facilities provided
Akbank with the ability to easily consolidate the diverse data sources.
• Integrated analytics — Datameer’s spreadsheet style interface, 270 powerful
functions and workbook linking enabled Akbank to consolidate their analytics
into a single suite.
• Speed and performance — Datameer’s ability to crunch through data and
analytics faster, allowed Akbank to speed the processing times.
• Agile approach to analytics — Datameer’s rapid data discovery allowed
Akbank to explore new problems and see new types of customer behavior.
Akbank used Datameer to deliver the desired agility with the marketing campaigns. Because of Datameer, analysts and campaign owners could see results daily and make required adjustments on-the-fly to increase the performance of their campaigns. Specific results include:
• The cycle time to run the analytics that covered the 90 different Akbank
marketing campaigns was reduced from 5 days to 5 hours
• Analytics spread across over 1,000 different SQL queries were consolidated into easy to use, templated analytics in Datameer
• Parameterized analytics centralized in Datameer eliminated errors and provided
governance to see lineage and track changes
• Four analysts that were previously continuously coding SQL queries were freed
to explore the campaign data looking for new behavioral insights
• The consolidated data and analytics now enabled analysts to explore customer
behavior across campaigns and get a customer-centric view of responses