www.elastic.co

C A S E S T U D Y

Using Elasticsearch, we help our clients generate insight and take immediate action based on vast amounts of data in real-time on their brand; customers; prospects; competitors; and related industry topics.

- Aaron Wallis, founder of Lexer

CompanyLexer

LocationAustralia

SegmentTechnology

Use CaseEmbedded Elasticsearch

LEXER BUILDS NEXT GEN SOCIAL LISTENING PLATFORM WITH ELASTICSEARCHSaves hundreds of hours of development time

How quickly can you stay informed about the conversations happening around your brand and competitors, both positive and negative? How simply can you engage with customers and prospects across paid, owned and earned media?

“

1 3 400Billion

of Total Number of Documents

TB

Total Data Size

Milion

Public data sources

Fortunately, a massive volume of publicly available data exists to help businesses recognise risk events and manage their brand accordingly. The pace and volume of information fl owing through these networks is unprecedented, meaning businesses have far less time to review, understand, identify, and action data that could be critically damaging to their business.

Lexer was created to solve this problem. This Australian SaaS company helps enterprise clients generate actionable insight from massive amounts of data; understand the context and authors of that content; and ultimately manage risk to brands and drive personalised omni channel marketing opportunities, ultimately increasing revenue and decreasing costs.

www.elastic.co

C A S E S T U D Y

“Our Enrichment Platform combines more than 400 million public data sources with a company’s proprietary CRM and Support data,” said Aaron Wallis, founder of Lexer. “Using Elasticsearch, we help our clients generate insight and take immediate action based on vast amounts of data in real-time on their brand; customers; prospects; competitors; and related industry topics.”

Putting this into context, let’s take the example of a dissatisfi ed bank customer standing in a long queue at their local branch.

The customer tweets from their place in line, and then cross posts to Facebook. On Facebook, the customer engages in long discussions about switching banks with her friends and followers. Friends-of-friends start chiming in, and the post also starts getting RT’d on Twitter. Both conversations are starting to spread throughout the two platforms as the message resonates with others. Less than 30 minutes have passed, and these original posts have been shared 200 times and seen by thousands. The bank teller who eventually serves the customer has no idea about this spread, and what kind of impact a remarkable experience for this customer could have for their brand

Let’s add a new element to this scenario - what if the bank was proactively monitoring in real-time every piece of public content published by every customer, the topics being discussed, and in all cases proactively engaged with each customer? The bank teller would have the support of their entire business in not just servicing this disgruntled customer, but delighting them.

Aaron Wallis explains how this is possible. “The aggregations feature in Elasticsearch helps us turn our growing data stream into bite-sized insights. These could be as unsophisticated as user profi le data, language, and time of day, up to sophisticated attributes such as geo data, and precise keywords or phrases.”

Introducing Lexer into our disgruntled customer scenario, a customer service representative could query their data in the following way:

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C A S E S T U D Y

Using enriched customer identities which are updated in real time, the customer service representative can explore the data and follow their engagement process and policies to engage directly with the customer.

In addition to the simple act of acknowledging the issue, the representative can also conduct deep level research and ask questions such as:

• Who else is seeing this content?

• What infl uence is the content having on our brand?

• Is the customer a regular complainer about products and services?

• Which of our products does the customer have?

• Is the customer a churn risk?

• Which channel is best to communicate with the customer and acknowledge the issue?

• Is there a relationship between complaints and lifetime customer value?

Elasticsearch has been evolutionary for our business. We’ve saved hundreds of hours of development time. Lexer can easily mine massive volumes of data in real-time, and using Elasticsearch’s aggregations has helped us to build a platform that provides critical predictive insights.

- Aaron Wallis, founder of Lexer

To learn more about Elastic, contact sales@elastic.co