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.


Do not use blank “campaignId” strings with Google Analytics tags

Sparkline were set with a curious challenge when one of our clients raised a problem with the Google Analytics Source/Medium report. The top Source/Medium by sessions was “(not set) / (not set)”. This was very, very unusual. We asked what could possibly cause GA to not recognise Source/Mediums correctly?

After some untangling, we discovered that the blank string had been set as the campaignId in the GA tags. Since GA couldn’t interpret the blank string, it simply saved the Source/Medium as “(not set) / (not set)”.

Read more »

How to accurately track clicks from aggregator sites


GoBear is an insurance policy and credit card research aggregator service. It is critical for GoBear to track the number of clicks directed to its partners’ websites. On the other hand, it is equally important for the partner (e.g. an insurance company or a credit card provider) to measure the number of inbound clicks from GoBear.

Gobear Search Results


When a user clicks on the “Go To Provider” button, GoBear tracks this as a “click out” on its end using event tracking. However, the partner also needs to keep track of the click that it receives using an equivalent metric.

“How can the partner track the inbound clicks from GoBear?”

The partner cannot rely on the number of sessions referred from GoBear because this will not be an equivalent comparison to GoBear’s clicks. If the user clicks multiple times within a short period of time, it will be seen as one session on the partner’s Google Analytics reports, but recognised as several clicks in GoBear’s reports. Also, not all clicks would be successfully directed to the partner site if users close their browser before the partner site loads.

Sparkline Solution

For tracking inbound traffic, the partner site can use a Custom Metric to track the number of inbound referrals from GoBear.

  1. Create a Custom Metric called “Lead Count” in Google Analytics (GA).
  2. Create a Constant variable to hold the GA index assigned to “Lead Count”.
  3. Create a Custom JavaScript variable called “CJS Lead Count” in Google Tag Manager (GTM). Depending on the Referrer variable, this will be set to 1 or 0.
  4. Set the “CJS Lead Count” in the GA Pageview tag along with its corresponding index.

Step 1:

Create a custom metric in Google Analytics following the steps in Google Help.

Step 2:

Create a Constant variable and set its value to the index of the Lead Count custom metric assigned in Google Analytics. Here, the index is assumed to be 2.


Step 3.1:

In GTM, configure the “Referrer” built-in variable.


For example, let us count the inbound traffic from “www.gobear.com/sg. The value of “Referrer” will contain “www.gobear.com”.

Step 3.2:

Create a Custom JavaScript variable with the condition to check if the referrer is the aggregator site (in our example, it is gobear.com) and set the counter value to 1 or 0 accordingly.

gobear_step 3.2


function() {
return {{Referrer}}.indexOf("gobear.com") > -1 ? 1 : 0;

Step 4:

Set this Custom JavaScript variable in the GA Pageview tag (reference: Google Help).



As a result of this, the partner-site will be able to track the number of inbound referrals from its aggregator sites. For example:


This will allow them to better compare click out metrics reported by GoBear instead of trying to reconcile session numbers.

Sparkline Shows Leading Indonesian Publisher, Kaskus, How To Increase Engagement & Revenue For Mobile Customers

KASKUS is a leading user-generated content publisher in Indonesia where users exchange information and buy / sell goods on forums. More than 90% of KASKUS users are Indonesian – of which most are young men. As of April 2015, KASKUS has at least 28 million unique users each month, making it the largest user-generated content publisher in Indonesia.

KASKUS wanted to serve its users relevant ads to their age, gender and interests so as to create better user engagement and higher-quality traffic for advertisers. Furthermore, they wanted to users who have shown interest in mobile devices and were more likely to purchase them.

KASKUS reached out to Sparkline in order to create a Google Analytics 360 segment for “Mobile Intenders.”

Sparkline was able to show the KASKUS team a fresh way to approach the challenge: Create a powerful new Google Analytics 360 segment for Mobile Intenders and ensure that it can be targeted within DoubleClick For Publishers (DFP)

In order to leverage their own audience data to serve the most relevant ads, Sparkline devised for Kaskus the following steps.

1.Set up Analytics 360 to collect valuable first-party data using Custom Dimensions. This feature enabled them to analyze data that Analytics 360 did not collect with a default implementation, such as Thread Id (unique forum thread identifier) and Forum Section (groups similar forums into sections such as Android and The Lounge).

2.Conducted a segmentation analysis by looking into the Analytics 360 data to understand user behavior on site through their interaction with mobile-focused forums. One particular segment emerged as potentially valuable, users actively searching for and discussing mobile phone brands and features for future purchase. Using Analytics 360 segmentation capabilities, KASKUS created an Audience of “Mobile Intenders” .

Kaskus Screenshot

3.Last, using the Analytics 360 Audience Sharing feature with Doubleclick For Publishers (DFP), the “Mobile Intenders” segment was shared with DFP Audience (and Doubleclick Ad Exchange) where advertisers are able to bid on the audience-targeted inventory directly.

The new audience KASKUS created in Analytics 360 was in high demand by advertisers and as it is available on DFP Audience, it can be targeted by programmatic advertisers, particularly by handset brands seeking to win consideration from users intending to purchase a mobile phone.

Sparkline were able to show KASKUS that by using Google Analytics 360 and DFP Audience together they could achieve a twofold CTR uplift and more than triple CPM on audience-targeted Ad Exchange inventory when compared to open-auction inventory.

To learn more about how KASKUS achieved those results read the full case study.

Google Data Studio now offers unlimited reports for free!

Yes, you read that right! Google has removed the 5 report limit on the free version of Google Data Studio. Users can enjoy the product with its full capability for free. This goes hand-in-hand with Google’s mission to “organize the world’s information and make it universally accessible and useful”.

What is Google Data Studio?

Google Data Studio is a reporting tool and is part of the Google Analytics 360 suite. You can create your own branded reports and dashboards and share it with your team. It seamlessly integrates with Google Analytics 360, Google Sheets, Google BigQuery, YouTube Analytics, databases and more. Data Studio converts the analytics data into informational, easy-to-understand reports through data visualization. Users can choose the types of visualization, such as charts, graphs, geo-maps, tables, etc.

A sample Google Data Studio dashboard (Link)

A sample Google Data Studio dashboard (Link)

Google Data studio is currently available in 37 languages and supports number, date, and time formats in those locales. Data Studio can also handle 59 international currencies. It is available in selected countries (list of supported countries) and will be made available in more countries moving forward.

Next Steps

  • Head to the official Google Data Studio website (link) to find out more about its features, resources, and examples.
  • Read through the official blog post from Google on the removal of the reports limit (link).
  • Contact Sparkline on how to make the best use of Data Studio with Analytics data!
Sparkline helps insurance meta search engine ​GoBear nail data analytics from the outset

Sparkline helps insurance meta search engine ​GoBear nail data analytics from the outset


In the first few years of setting up a business, there are so many things for a fledgling company to think about – hiring, managing cashflow, growing sales to name a few. The notion of analysing their customer data from the outset by making sure they have the right measurement tools and processes in place can appear just too daunting or is unlikely to register as a priority. However, taking steps at this early stage in a company’s development to get data analytics right can pay dividends and avoid a lot of headaches further down the line.

As a start business, GoBear had the foresight and engaged the technical and analytical support from analytics consultancy Sparkline, to enable them to get it right from the outset.

Sparkline helped GoBear in building dashboards and setting up Google Analytics Premium to gain deeper insights on user behaviour on the GoBear website.


Launched in early 2015, GoBear is an insurance search engine that allows users to browse for car, travel and health insurance via price and usage. It does not sell insurance directly – users are automatically transferred to the insurer’s or agent’s website to make their purchases. GoBear is headquartered in Singapore and its team has been chosen based on experience, knowledge and ambition to actively transform the process of online shopping by offering a fast, concise and coherent comparison of car and travel insurance plans.

Headed by Andre Hesselink, this free service compares hundreds of insurance policies, providing users with a transparent and unbiased comparison of prices, coverage and other policy features in just a few seconds.

GoBear realised that Singaporeans were not just interested in the cheapest plan, but the plan that represented the best value for their needs. This, coupled with a user-friendly site (both on mobile and desktop), is the heartbeat of GoBear’s vision and strategy. The mobile and tablet-friendly GoBear platform allows users to compare the car and travel insurance offerings of a variety of companies and then purchase the chosen plan, all on a single platform. Some of the insurers on GoBear’s platform include Citibank, UOI, MSIG, QBE, NTUC Income and Great Eastern to name a few.


Having worked in previous online ventures for many years, Hesselink was already aware of the importance of data analytics to the growth of the GoBear business.

However, there was a recognition that greater customization of their analytics capabilities was necessary to ensure a positive online experience for customers from the outset, particularly as purchasing insurance online is still a new concept for many Singaporeans used to buying insurance through a physical broker.


To help them develop the level of customization required, GoBear brought in the team at Sparkline. Sparkline implemented Google Analytics Premium as the central analytics platform to provide a greater understanding of customer behaviour and preference. The implementation was customised to align with GoBear’s key business objectives.

Sparkline then created a customized dashboard for GoBear, built on top of the Google Analytics Premium (GAP) API, simplifying the monitoring process and enabling the team to analyze customer behaviour as they navigate through the site.

The dashboard provides a visualization of how users are interacting with the GoBear website and which areas of the user experience require attention.


What began as an engagement for Sparkline helping GoBear to implement Google Analytics Premium, grew into a consultancy which helped GoBear leverage actionable insights from the data to improve customer and business intelligence.

As a result of having access to Google Analytics data and dashboards, GoBear now has insights into how users are interacting with the site, thereby offering GoBear users an even more enriched experience.

The dashboard provides the GoBear team an overview of the key metrics, with presentation customised to their business model, that has helped in quicker and more relevant decision making.


As a company that’s based online, understanding user data is a key component in our business in order to get insight into what our users want, and how we can improve to help them even more efficiently. Sparkline has been integral in supporting our growth.

Andre Hesselink, CEO