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Sparkline helps insurance meta search engine GoBear nail data analytics from launch date


Data-driven from the very beginning

Having worked in previous online ventures, CEO Andre Hesselink was aware of the importance of data analytics to the growth of the GoBear business. He wanted to ensure a sound analytics architecture was in place before GoBear was launched. However, greater customization of their analytics capabilities was necessary to give his team insights into how to create a positive online experience for customers while capturing unique customer insights to insurance companies partnered with GoBear.

To achieve the level of customization required, GoBear tasked Sparkline, a certified Google Analytics Partner, to implement Google Analytics as the central analytics platform to provide a greater understanding of customer behaviour and preference.

Data at GoBear’s fingertips

Sparkline’s hands-on advice on web analytics infrastructure meant that GoBear could roll out their website fully confident of its data infrastructure and analytics capabilities from day one.

Sparkline went on to create an executive visualisations, leveraging Google Sheets, Google Analytics Core Reporting API, and Google BigQuery, to allow key data to be shared across the organisation instantly.

This customised dashboard freed up at least 20% of their analysts’ time, allowing them to focus on acting on the data rather than extracting it.

About GoBear

Headquartered in Singapore, GoBear is an insurance search engine that allows users to browse for car, travel, health and home insurance products via price and usage.

To learn more, visit

At a Glance

– Ensure Google Analytics was customized and properly implemented based on their business goals to capture the most effective site data

– Gain a greater understanding of customer behavior and preferences via data analytics

– Implement Google Analytics as the central analytics platform

-Create a customized dashboard to analyze customer behaviour as they navigate through the site

– Custom implementation of Google Analytics achieved within project timelines

-Executive-level dashboard visualizing key data points to enable management teams to quicker and more relevant decision making

KASKUS Doubles CTR and Triples CPM With DoubleClick for Publishers and Google Analytics 360


With so many users, KASKUS recently faced a growing challenge: how to serve its users ads relevant to their age, gender, and interests. “As KASKUS is the leading digital community and social commerce platform, our vision is to drive data-driven monetization by making our first-party audience data actionable,” said Ronny W. Sugiadha, chief marketing officer for KASKUS. “We want to give advertisers ways to perform better on our sites and increase the effectiveness of our impression-based ads.”

With guidance from Sparkline, the KASKUS team began using their own audience data to serve the most relevant ads.

Set up Analytics 360 to collect valuable first-party data using custom dimensions.

Ran a segmentation analysis of their Analytics 360 data to understand how on-site users interacted with mobile-focused forums.

One segment looked especially valuable: users actively searching for and discussing mobile phone brands and features for future purchase. Analytics 360 has segmentation capabilities that let KASKUS create an audience it called Mobile Intenders.

Used the Analytics 360 Audience Sharing feature with DFP to share the Mobile Intenders segment with DFP Audience and DoubleClick Ad Exchange.

This new Mobile Intenders audience was soon in high demand by advertisers. Available on DFP Audience, it can be targeted by programmatic advertisers, particularly by handset brands that want to win the attention of users intending to buy a mobile phone.

How well did the new segment work compared to its old open-auction inventory? ”

“Using the Analytics 360 Audience Segment sharing feature in DFP and AdX, we doubled our CTR and saw a 3.3X CPM uplift on this audience-targeted AdX inventory,” Ronny Sugiadha reported. “We are looking forward to even more positive impact moving forward.”


KASKUS—the largest Indonesian community including social commerce— With more than nine million registered members that make up more than 20,000 communities, KASKUS provides online forum for discussion and platform for buying-selling transactions. KASKUS now can be accessed through its website, mobile web, and mobile applications.

To learn more, visit

At a Glance

Serve KASKUS user’s ads relevant to their age, gender, and interests to create better user engagement and higher-quality traffic for advertisers.

-Paired custom dimensions and KASKUS first-party data from mobile-focused forums
Used Google Analytics 360

-Audience Sharing to bring the new Mobile Intenders segment to DoubleClick For Publisher (DFP) and Ad Exchange (AdX), where advertisers can bid directly on it

-2X click-through rate (CTR) uplift
-3.3X CPM uplift

Standard Chartered Bank implemented new analytics tools across nearly all markets in a 3-month period

Challenge: Internally named ‘Project Dire Straits’, Standard Chartered Bank (SCB) embarked on a project to switch their analytics platform to Google Analytics. The project impacted 60 web properties used by consumers, investor relations and online banking in 40 countries as well as cross-location staff from several departments. To deliver a project of this size and scale would normally take 6-9 months. SCB brought in analytics experts Sparkline and set a project timeline of 3 months.

Aim: Sparkline developed a customised code in Google Tag Manager to ease cross-market implementation, then fully rolled out Google Analytics and Google Tag Manager functionality. Most importantly, data quality was maintained throughout the migration allowing SCB to acquire accurate new data sets through demographic reporting and attribution modelling. Sparkline delivered training for SCB staff based in APAC, Africa and the Middle East.

End Result: Sparkline’s agility ensured the 3 main project components; migration, implementation and training were delivered within 3 months without data quality disruption. This success has allowed SCB to deliver improvements to their online banking and product offerings almost immediately and maintain reporting consistency across multiple teams and countries.

About Standard Chartered Bank

An international bank present in 70 countries, with a focus on Asia, Africa and the Middle East.

To learn more, visit

At a Glance

– Switch analytics platform to Google Analytics

– Implement the change to over 60 web properties across 40 countries

– Train globally located staff

– Maintain data quality

– Project timeline of 3 months

– Develop custom codes within Google Tag Manager

– Roll out Google Analytics

– Migration, implementation and internal training delivered within timelines

– Data quality maintained

– Ongoing relationship established

Sparkline Helps Reebonz achieve +50% ROAS uplift with Google Analytics 360


Fashion savvy consumers across APAC , looking for the latest range of luxury products turn to Reebonz for their online shopping needs. Founded in 2009 the company currently attracts hundreds of thousands unique monthly users a month looking to buy and sell luxury products.

With users having the option to engage both on web and mobile, Reebonz faced the challenge to understand what role each platform had in the purchase cycle.

Gaining a Single View of the Customer
Reebonz turned to Sparkline, their Digital Analytics Consultants, to understand how they could gain better clarity across devices and where to invest their ad dollars for maximum impact. Sparkline recommended using Google Analytics 360 to implement a single view of a customer across devices. They also worked closely with the Reebonz team to incorporate app & web tracking on a single property via User ID.

Upon set up, the analysts at Sparkline investigated the data and found that when mobile web is part of path to purchase, conversions improved dramatically by up to 2.8x.

Armed with this knowledge, Reebonz implemented a robust marketing approach which increased cross device conversions 2x and had an overall +50% Return On Ad Spend on search advertising.

About Reebonz

Reebonz is a trusted online platform for buying and selling the widest range of luxury products.

To learn more, visit

At a Glance

– To understand shifting individual user behaviour across platforms and apply this to advertising spend.

– Implement Google Analytics to ensure after users login successfully, their user ID is tracked to GA allowing for segmentation and analysis for logged in users (“members”) across devices.


-55.4% increase in ROAS in SEM

-20% increase in transactions in SEM

-The solution and analysis methodology is now replicated across all Reebonz markets

“Users have multiple ways of engaging with Reebonz to sell and buy products. Understanding how best to target users working across devices, by adjusting our advertising is an important step in Reebonz’ marketing strategy . By working with Sparkline and Google we were able to understand this shift and act on it. With over 50% ROAS uplift on search, we are extremely happy with the results.”

– Ben Han, Co -founder,

dtac Users Frequenting the Community Page are Quality customers

At a Glance

GOALS: dtac wanted to understand the role that the Community page plays with regards to users who converts on dtac.

APPROACH: Through a segmentation analysis, dtac was better able to understand the value of their community users in terms of loyalty, engagement and propensity to purchase on site.

RESULTS: dtac placed more emphasis in monitoring & engaging with their community users who were shown to be a high-value segment.


Understanding and utilizing data
In a market where users are more inclined to be involved in the online community than ever, dtac recognised the importance of finding out the role that their Community page has in driving users towards their products and offerings.

Traits of users on the Community Page

  • They are very loyal users of dtac. 95% of whom are Returning users.
  • They are highly engaged: spending 3X longer on the site (6 mins); looking at 4X more pages per session (10 pages / session); and a lower Bounce Rate of 18%.
  • These users also spend more with dtac: up to 70% higher AOV; and their monthly phone bill is 50% higher compared to an average user.
  • They are twice twice more likely to purchase a mobile device from established brands (i.e. Apple, Samsung).

Moving forward
With the data and analysis in hand, dtac can now serve personalised ads using Audience segments to increase conversions. Also, they can now target look-alike audiences that are more likely to become high-value.

About dtac

Total Access Communication Public Company Limited, commonly known as DTAC, is the third-largest GSM mobile phone provider in Thailand after AIS. DTAC is owned by Telenor both directly and indirectly, and both companies share the same logo.

To learn more, visit www.dtac.co.th


Genesis Energy Increases Revenue through Online Channel

Genesis Energy’s improved online experience, powered by analytics, has increased the company’s sales performance through the online channel.

The Problem: Genesis Energy had high volume of activity on their website, however these visits were not converting into sales. To better understand user behaviour, roadblocks and drop off points they brought in analytics experts Sparkline.

The Solution: After setting up Google Tag Manager across every page of the Genesis website, Sparkline implemented Google Analytics. By using the events and custom dimensions functionality, every action on the site was captured allowing Genesis to study user behaviour and related patterns. Analysing drop off points, the online customer signup form was identified as a roadblock to conversion.

The Results: Genesis responded quickly. Better understanding of user behaviour and taking action to simplify the customer signup form improved sales through the online channel by $NZD4M. Genesis now plan to implement Google Analytics Premium, DoubleClick integration, segmentation and optimisation of the customer lifetime value, for more control and ongoing insight into their customer data.



About Genesis Energy

New Zealand’s largest energy retailer, selling utilities to 650K homes. In 2013-14, the business serviced 26% of the retail electricity market and 42% of retail gas while also producing 14% of New Zealand’s electricity.

To learn more, visit www.genesisenergy.co.nz

Amari’s bookings increase 47% with Google Analytics’ Attribution Modeling Tool

Amari is a hotel brand owned by Onyx Hospitality Group. The company had been evaluating the effectiveness of its marketing channels based on last-click attribution, but this was proving problematic. Intuitively the team knew display marketing was an important channel contributing to the business, but the last-click model made this difficult to quantify, hard to prove, and even harder to optimize. They have turned to Sparkline to help quantify this intuition and access measurable insights.

Attribution models to fit
We proposed solving Amari’s issue through the use of Google Analytics’ Attribution Modeling Tool and Multi-Channel Funnels. The team used the Attribution Modeling Tool to build, customize, and compare attribution models for Amari’s digital marketing activities. The aim was to apply these models in order to reveal the impact of the company’s diverse marketing efforts, specifically how these worked together in driving sales and conversions. It used Google Analytics’ Multi-Channel Funnels to uncover how much assistance each channel contributed towards conversions, and leveraged the Attribution Modeling Tool to assigning a non-ambiguous monetary value to those assists.

The initial challenge was discovering what model to use. After in-depth experimentation, the team decided to utilize the linear and time decay
models. The linear model equally allocates the value of a sale across all touch points, while the time decay model allocates value in favor of touch
points closer to the time of conversion. By using a combination of the two, Amari’s digital marketing team could assess channel effectiveness both on
an egalitarian basis and by showing preference for those who drove valuable traffic more recently.

“We have successfully shifted from the outdated last-click attribution towards a more holistic model that helps us optimize marketing accountability and, more importantly, profitability,” explains Chutima Fuangkham, Director of Digital Marketing for Amari Hotels. This has allowed Amari to confidently increase its display marketing budget. Overall, by increasing investment into undervalued marketing channels, Amari has achieved a 47% boost in bookings.

Read the full case study here.

About Amari 

Amari is a hotel brand owned by Onyx Hospitality Group. It provides full-service hotels and resorts, serving business and leisure guests. For more information, head to www.amari.com

Ask and Get Insights on the fly with Google Analytics Intelligence

This post shares about a summary of what the Google Analytics Intelligence “Ask a Question” and “Automated Insights” features bring to the table for analysts and business users, how to use them, what some limitations are and how these features impact businesses today.
Photo: MarketingLand

We take a look at the latest Analytics Intelligence features released: Ask a Question and Automated Insights help users to ask for and receive “plain English” questions and answers via artificial intelligence.

Know what data you need and want it quickly? Just ask Google Analytics Intelligence and get your answer.

If you are new to using Google Analytics (GA), navigating the web platform and understanding all its terminology can be quite overwhelming. And if you’re not, here’s a truth about GA that many users might be able to relate to: unless you have deep familiarity with the tool or use it regularly enough, finding the information that you need in GA can often pose as a challenge. The sidebar menu on the left of the GA interface can be somewhat difficult to interpret or navigate for the occasional user, who may waste a lot of time poking around in report categories such as “Audience,” “Acquisition,” “Behavior” and “Conversions” to find the exact data that he would need for gathering insights.
These group of users, would then most probably approach the analyst team to get some help in getting the insights faster. A team at Google recently spoke to web analysts and indicated that they spend “half their time answering basic analytics questions for other people in their organization.” A report from Forrester found 57% of marketers find it difficult to give their stakeholders in different functions access to their data and insights.
Today, Google Analytics Intelligence latest “Ask a Question” and “Automated Insights” features aim to make it easier for people to be able to get the information that they require without needing to be well-versed with the Google Analytics interface or without having to be dependent on analysts. By asking a question in Analytics Intelligence in plain English, it is possible for business users and analysts to obtain analytics data easily and get access to the information that they need more rapidly, providing these both groups of users the ability to focus their energies on strategy and higher-value aspects of their roles.

What is Analytics Intelligence?

Analytics Intelligence is the umbrella term for a set of Google Analytics features such as Smart Lists, Smart Goals and Session Quality that use machine learning to help users understand and act on their data more efficiently on both the web interface and mobile versions (Android and iOS).

How do I use it?

On desktop, users will be able to see automated insights and type questions into a query box after clicking the “Intelligence” button in the GA toolbar on the top right hand corner.

Source: periscopix
By clicking on this button, it will open up the Analytics Intelligence side panel and here users can have access to the two new features of Analytics Intelligence, “Ask a Question” and “Automated Insights”. So what do they do?

Ask a Question Feature

Source: Google Analytics
Using Natural Language Processing, the “Ask a Question” feature in Analytics Intelligence provides an easy and clean interface to ask questions of your data. There is no longer a need for users to require deep background knowledge of GA reports to find out what they are looking for, as they can simply ask GA what they want to know and the relevant data will be pulled as answers to their queries. It can be likened to Siri or Google Now, within GA.
Ask a Question understands all standard GA dimensions and metrics. Additionally, it is able to pick up on the various naming conventions that are unique to your account. For example, it knows about all those Custom Dimensions and Event Labels you’re using.
However, one thing to note is that this feature is only available for English language users at the moment, but Google says it will add other languages as the system learns more about the types of questions users are interested in moving forward.

Source: WSOL Blog

Automated Insights Feature

The other main feature of Analytics Intelligence is “Automated Insights”, which will look through all your GA data and try to surface any trends, patterns or changes that may be hidden within reports.

Source: periscopix
In each of these insights, Analytics Intelligence will display the relevant data and provide a recommendation course of action to take. For example, these actions can be:
  • “To learn more, create a Segment with sessions that include: Device Category: mobile”
    (From the insight: Your site performs below average on mobile)
  • “Consider including these landing pages in your AdWords campaign strategy”
    (From the insight: Some high performing organic landing pages are not backed by AdWords campaigns)
The good thing is that you are able to save these Insights for later, and by doing so this insight will be pinned as a query to the Insights bar. Whenever you open your Analytics Intelligence, you can easily select this question to ask again. As these saved insights would be linked to your account, you do not have to worry about them being visible to any other users who have access to the GA property.
Source: periscopix
The goal behind these new features is to give the analysts and decision makers the information they want more quickly so that more time and resources can be spent on making use of the data for a positive change.

What kind of questions can I ask?

Currently, “Ask a question” supports typically “what” and “how many” types of questions about the data that GA knows about your business. These can include segments as well. For example, displaying sessions for the month segmented by age. Analytics Intelligence would then display the results with a chart, saving the user several clicks of effort and time spent digging.
Additionally, you can also ask follow-up questions based on the previous question you typed. There are suggested questions that display once a user clicks in the query box as prompts.

Source: WSOL Blog
Among the types of questions Google says users can ask Google Analytics:
What do you want to do?
You can try asking…
Basic reporting
“How many users did we get yesterday?” “Where is my traffic coming from?” “How many new users did we get last week on mobile?”
Check performance
“Which channel converted the best for [Goal X]?” “Which landing pages with over 500 sessions have the worst bounce rates?”
Chart trends
“Trend of new users this month?” “Graph of sessions from Chicago vs Seattle in December?” “Percent of Direct traffic over time?”
Compare data for different values or time ranges
“Conversion rate for referrals vs organic search?” “Average time on page for mobile vs desktop?” “How many [EventAction] did we have in February vs January?”
Ask about shares or percentages to understand significance
“Share of sessions by browser?” “What percent of sessions in the U.S. are from social?” “What share of sessions are from women?”
Ask complex questions combining multiple phrases
“How did share of new users compare in January for Firefox vs Chrome?” “Trend of new users this year vs last year”
Source: Google Analytics
Furthermore, they have several questions recommended for different groups or industry of users:
Which group of users do you belong to?
You can try asking…
For e-commerce websites
“Which products had over 200 unique purchases?” “What is our conversion rate in Spain?” “Share of revenue by country last quarter?”
For advertisers
“Top campaigns by [Goal X] conversion rate?”“Which banner ad content performs best?” “Which paid search keywords convert the best?”
For publishers
“Which [Custom Dimension for Article] got the most views yesterday?” “What share of people on [Page] are female?” “Trend of pageviews for [Author X]”
Source: Google Analytics


At this time, Analytics Intelligence aims to answer questions about your historical Analytics data and is not currently able to answer questions related to the following:
  • General support (e.g. “How do I build a segment?”)
  • Explanations (e.g. “Why is my bounce rate increasing?”)
  • (Note: This limitation will be removed in the coming months.)
  • Strategic advice (e.g. “Which campaign should I invest in?”)
  • General search (e.g. “What’s the weather like?”)
Additionally, there will also be cases when Analytics Intelligence could not understand the terms or grammar used in your question and will be unable to answer.

What does this mean for businesses?

At present, Google Analytics have been already tracking massive amounts of data and generating reports for analysts and business decision makers. Now, this feature allows users across the organization to have the ability to surface insights in a quick-to-read format so they do not have to click around to navigate different pages to find these information, which make online business website performance tracking easy and saves time for more demanding or strategic tasks.
Specifically for larger companies that have a data analyst or team of analysts, these insights should help them scale up. And for smaller businesses that can’t afford their own analysts, this approach could bring that same type of possibility of having these analysts accessible to them and bring in insights that might be missed otherwise.
Does this mean that Google is killing the role of the analyst? While the Analytics Intelligence feature is impressive, one important factor to consider is that it cannot tell users what questions to ask in order to serve its business context best.
One of the major challenges that companies face today is that as the volume of data is increasing and more sophisticated tools made available for analyzing it, those data and tools are of minimal utility if the people using them don’t use the right metrics and ask the right questions.
Getting the most out of utilizing GA often requires a certain level of domain knowledge and experience that many organizations may not have and this may cause many in failing to maximize the value of this free tool. However, Analytics Intelligence may not fully be able to replace the role of an analyst as it is unable to tell users what they should be asking or what they should find out to be of real value to the business. In such cases, it is unable to suggest better and more relevant questions as well because it does not know what those questions are.
Furthermore, an example of a strategic question that Analytics Intelligence cannot answer is “Which campaign should I invest in?”. It is important for users to note that while the ease of using this new functionality provides a range of benefits, it will not help if it is used to produce reports and charts that do not actually help answer the key business questions at the end of the day.


Turning Big Data into Black Gold

Turning Big Data into Black Gold

Ninety percent of the data that exists today has been created in the last two years. In the time it took you to read that last sentence, 11.6 terabytes of data were generated. That is equivalent to about 17,400 CD-ROMs (if you remember what those are!). We live in a connected world, with a proliferation of devices that connect online. For the modern marketer, this means access to large volumes of data. If you believe in the saying that data is the new black gold, then marketers have struck it rich! Right? Unfortunately, this is not always the case.