Marketing to the “Long Term Memory” – How to Not Waste Advertising Money

brain long term memoryimage source:

Our brain contains two types of memories, which are short-term memory (or working memory) and long-term memory. Short-term memory is the short time we remember something before either dismissing it or transferring it to long-term memory. As marketers, we don’t want only to talk to short-term memory and waste our effort. Before everything, it is important to understand the memory type and its behavior.

Short term memory can be trained using “Maintenance rehearsal” which is a memory rehearsal that stores information into the short-term memory, but it is not an effective way store information into long-term memory. Long-term memory can be trained using Elaborative rehearsal, which is an effective way to transfer information into the long-term memory. Elaborative rehearsal involves thinking about the meaning of the information and connecting it to other information already stored in the memory. It goes much deeper than maintenance rehearsal.

A few important characteristics of long-term memory help marketers to pass their message to potential customers’ long-term memory

  • Related information and Storytelling – Elaborative rehearsal involves thinking about the meaning of the information and connecting it to other information already stored in the memory.
  • Visual long-term memory has a massive storage capacity for object details. (Standing, 1973)
  • Multi-channel and multi-device – Engaging with the material in more than one way encourage elaborative rehearsal.

Related information and Storytelling

Google has a very data-led culture. However, we care just as much about the storytelling and the brand, and how we tell the world about our mission. (Lorraine Twohill, Google’s senior vice president of global marketing). This indicates that Google understands the value of passing information to the long-term memory.

Emirates airlines’ cabin crew performed during a break in the game at Germany’s Volksparkstadion football stadium in Bahrenfeld, Hamburg, Germany to create the awareness of flight safety in front of 60,000 people. This is a very effective way to communicate the brand to the long-term memory with something already in the mind, which is football.


long term memoryWatch the video here: Link

 Visuals – “A picture is worth a thousand words”

Several campaigns proved that image ads are more effective than text ads in most cases. However, use images wisely. An image relevant to something in a mind could be a powerful way to communicate a message, rather than a generic image.

ReapDigital Facts: Personalized image ads based on designations/company provided above average return for the invested money. Personalization Case Study Here

Among the images, the human brain has a separate section to identify the faces above all other objects, so the face is a very powerful instrument to use in marketing activities. (Let’s discuss this in a separate article)

Multi-device and multi-channel campaigns

Marketers get access to customers’ long-term memory by reaching them using multi-channel and multi-devices. This is not a new concept, but doing it right is not common. A proper nurturing process can communicate the message to the long-term memory.

ReapDigital Facts: The team found that 90% of the conversion through (Thanks to Google Analytics Cross Device Tracking)  mobile campaigns happens using the desktop. People click the ads on mobiles but complete the transaction on a desktop. (Found across few clients.)

Don’t waste your money with short-term memory, hit the long-term memory with every cent you spend.



Multi-Property Attribution Model –Hotel Marketers Can’t Ignore It Anymore

Measuring campaign success across multiple channels is essential to gaining insight to invest on each channel. Nowadays, common buzz word is multi-channel attribution, even though marketers don’t practice it. Multi-channel attribution discusses profitability of each channel while considering the channel position in the customer’s journey. Channel positions vary from the first click, last click through to view through. Finding the right attribution model is quite challenging but once you have found it, doors will be opened to maximize the revenue while at the same time reducing the cost per acquisition. Apart from the multi-channel attribution, cross device attribution provides insight to allocate budgets across devices and to optimize campaigns to generate better returns.

Now it is time to introduce a new concept to measure the profitability across websites/properties. Modern customers go through multiple properties before they eventually make a purchase. Right now it is not possible to use multi-channel attribution modeling to solve this problem, as customers don’t click on a link to move from website to website. Let’s see an example in the travel vertical below.


Multi-Property Attribution OTAs

The customer starts the journey with TripAdvisor and reads a review then goes to the hotel website to get the information. Finally, they close the deal with as he is a loyal customer. The conversion will be attributed to the last engaged website which is and you can’t see the impact of various websites beyond with the existing analytics tools. In this case, the hotel website supports in creating the awareness (assisting) while Agoda closes the sale (last click). Multi-property optimization allows users to identify the real contribution of each websites.

It is important to quantify the impact of each customer engagement so that marketers get the opportunity to allocate a budget to each campaign. Let’s consider the same customer journey with hypothetical numbers. Let’s assume a hotel room is priced at $100 and the hotel owner pays 15% commission to

Scenario 01: Without Driving Traffic to the hotel website

The Hotel Owner makes money entirely from with no investment on the website.

Website and OTAs

 Scenario 02: Customer Drive Traffic to the Hotel website

Hotel owners expect to keep the cost per acquisition below $30 with paid campaigns. However, hotel owners don’t have a way to figure the multi-property attribution with the existing tools. The owner might’ve spent $1,000 on paid campaigns and only received 10 conversions from the website. Based on the campaign statistics, the cost per acquisition (CPA) for the campaign is $100 which is not profitable, as he previously expected. A marketing consultant would recommend him to stop the campaign immediately.

Paid Traffic to Site

 Quantifying the Multi-Website Attribution

If we have a mechanism to quantify the multi-website attribution then it allows us to identify the true impact of the campaign. Let’s consider the impact of the above campaign. drove an additional 30 conversions. Now, we have 40 conversions as a result of the paid campaign and it reduces the CPA to just $25. Yes, now the hotel owner has a profitable campaign and the hotel owner can expand it to maximize his revenue. This is the insight that we can extract from a multi-property attribution model.

Multi Property Attribution


Multi-channel and cross device attribution can be analyzed through Google Analytics and other similar analytics tools in the market. However, it is challenging to build a tool to find the attribution across websites for which we don’t have access. Good tagging framework won’t help us to solve this problem unless we have a mechanism to share a unique identifier across the customer. As a solution, we can use mathematical models such as regressions analysis to figure the revenue relationship between the hotel website and the (as in the example). Apart from that, there are websites that provide the complete user journey and they are able extract user data from their add-on users. Finally a multi-website attribution is a model that marketers can no longer ignore.

Data shows that Mayweather won the Google and Manny won the Twitter

Based on the Google trends, search queries for Mayweather is higher than Manny.

mayweather won the GoogleTwitter hash tag analysis shows that Manny got the highest number of tweets. This is based on a sample size of 6000 tweets with the hash tag #pacquiaovsmayweather.

Manny won the Twitter

Note: Twitter data could change based on the hash tag. #pacquiaovsmayweather could be  a popular has tag among Philippines than US.




Read Google Analytics Client ID(CID) Using Google Tag Manager and Assign to a Custom Dimension

Google Universal Analytics has introduced client id as the cookie variable. Client id is a unique identifier for each user or a browser. If we are able to track the cid as a custom dimension in the universal analytics then we can find the individual action of each visitor such as pageview, events etc…

With the each customer behavior, we can introduce the predictive analysis or data analysis to make actionable insights. Market basket analysis(associate rule) helps us to determine the common pages of each visitor before they complete a goal and such information lead us to create insightful remarketing campaign to expedite the conversion process through the funnel. Without knowing the each customer path, it is difficult to identify the value of a each page or identify commonalities of each customer path.

Through Google Tag manager we can read the cookie id of visitors and assign it to a custom dimension. Use following code in a custom html tag to read the cid

function readCookie(name) {
var nameEQ = name + “=”, ca = document.cookie.split(‘;’), i = 0, c;
for(;i < ca.length;i++) {
c = ca[i];
while (c[0]==’ ‘) c = c.substring(1);
if (c.indexOf(nameEQ) == 0) return c.substring(nameEQ.length);
return null;
var user = readCookie(‘_ga’);
if (document.cookie.indexOf(“_ga”) >= 0) {
dataLayer.push({‘readCookie': user});
dataLayer.push({‘event': ‘Cookie Set’});

Afterward create a custom dimension as below

And create a rule as below to fire

Custom report can be used to read the report and to take insight

That is all for the cookie ID configuration and lets meet with another article to explain the user behavior analysis.



Google Analytics Smarter Remarekting Guide

Recently Google launched smarter remarketing with Google Analytics. Now we have three types of remarketing lists.

  1. General Remakreting
  2. Similar audience adwords
  3. Smarter remarekting Google Analytics


General remarekting

General remarekting lists can be built with Google Analytics or with Google Adwords. Advertisers are smart enough to leverage visitor data to target them timely with very relevant offers. In hotel industry we can capture searched date and target them until that date to reduce the unwanted cost and to maximize the ROI.

Similar Audiences

Once we create the audiences within Google Adwords, it automatically create the similar audience list based on visitor activities on other sites.

The “similar audiences” feature enables you to find people who share characteristics with your site visitors. By adding “similar audiences” to your ad group, you can show your ads to people whose interests are similar to those of your site visitors, which allows you to reach new and qualified potential customers.

AdWords looks at browsing activity on Display Network sites over the last 30 days, and uses this, along with our contextual engine, to understand the shared interests and characteristics of the people in your remarketing list.

Smarter Remarketing

Smarter remarekting use visitor engagement with other sites that allowed to share data anonymously. This is a good opportunity to target  visitors who visits competitor sites.

Smart Lists are built using machine learning across the millions of Google Analytics websites which have opted in to share anonymized conversion data, using dozens of signals like visit duration, page depth, location, device, referrer, and browser to predict which of your users are most likely to convert during a later visit.

Small smarter analytics guide will help you to built your first smarter remarketing campaign

Obama’s name and face photo can be used in Google ads

Google is to launch face photo option within the Google ads but funny thing is people can use fake photos to motivate users to buy their product. For an example they can use celebrity photo to review about beauty products.

I just created an image using Obama’s face to demonstrate the concept. Anyway I believe that they will create better ad solution as always.




Consider Attribution Model before Optimize for Offline Sales with Adwords

Google has introduced offline conversion tracking for Adwords. It is said to become a big influence in many businesses that deal with Adwords. We had a chance to measure offline conversions with universal analytics and import them to Adwords, but there were few difficulties to do so. Google Analytics records last click attribution on default reports so we need to look at multi-channel reports to identify the actual contribution from PPC.  Creating additional profiles and filters there are possibilities to identify PPC keywords without dealing with multi-channel reports but it isn’t a simple task to do.

This is great news for those who work with Adwords.  You will now be able to track offline conversions for Adwords without extra work being required with use of Google Analytics.  Click ID is a new element associated with offline conversion tracking. Click ID allows your website to assign a certain ID number to each lead that is received through your clicks, such as, sign ups and downloads. After your customer completed the conversion, your conversions can be directly uploaded by using the click ID so that Adwords can identify your conversion to show actual conversions and revenue. It is required that a primary key be used to “link” the offline sale to the online click and you may use email, passport id or phone number.

Benefits of offline conversion tracking are listed below:

  • Consider Actual sales value not leads
  • Understand the keywords that drive the most profitable sales
  • More accurate ROI picture
  • Manage bids and budget to drive actual sales

Here is an example of how it can work for you:

You own an online taxi service and you do your advertising using Adwords to help in generating your customer sales leads. A customer will request a quote from you first on your website; however, payment will not be received until you take the customer to their destination. In this situation, you must measure actual conversion with actual value. Up to now, you would be able to track all the leads with average order value not the actual sales. This is where this could be a big problem solver for you. Using offline tracking you could identify actual keywords that drove the sale.

How to use Adwords offline conversion tracking?

In the above example, the “Primary Key” can be the email address or phone number of each customer.

Don’t depend on Adwords Offline Tracking

Adwords offline tracking can be used to provide you with actual cost and actual income; however, this doesn’t always give you the final picture of what your total cost will be. If you have spent $100 on Adwords and that allows for $200.00 in sales and you also matched the sale using from Adwords offline conversion tracking. That shows you $100 in profit. But you would need to add all the cost that you spent on each channel to bring that sale.

When we analyze the multi-channel attribution with Google analytics, we can identify that there are other paid channels that helped to complete the conversion. This would show you that you don’t actually make $100 in profits from this even though Adwords said that you did. You must consider the cost of the other paid channels as well.

Above example shows that Social Media and Adwords are profitable when they consider as an individual channel but after plotting the sales path you will figure out the conversion isn’t profitable as you think.

Relying completely upon Adwords CPA is never recommended and it worths to look multi-channel attribution to understand the actual picture.

If you have any questions or suggestion please use comment box or contact me link.

Speaking Engagment with Google Day Sri Lanka

Google Sri Lanka has organized G|Day program to transfer and share knowledge to Sri Lankans. There were two sessions in the program, one program from GBG and another program from GDG that is Google Developer Group. I got an opportunity to speak in GDG about App analytic using Google Universal Analtycis. Audience had good understanding about Google Analytics but unfortunately only few developers had experience with implementation of Universal Analytics. I think the presentation will help them to uncover opportunities with universal analytics and to understand the importance of the data driven decisions. covered the entire session and included the speech in their blog (Find it below)

Dinesh now steps off stage and Niroshan, a seasoned Google Analytics specialist takes the stage to talk about how you can improve your app’s performance via analytics. According to Niroshan, in the life cycle of an app, marketing and monetizing is the hardest part of the life cycle.

Niroshan, gives an example of a famous hotel that used analyitcs, which resulted in the hotel’s sales gain a massive jump and also result in it getting an even larger revenue. Niroshan states that, when using analytics, it’s possible and important to measure and pay attention to data and before making big decisions.

Niroshan now moves on to talk about how to measure an app’s value which is by: understanding it’s value which is measured by downloads along with new/old users, engagement which is measured by app crashes and events, and finally the outcome which is basically how much money you get from the app.

Niroshan now moves onto talk about using  Universal analytics to measure app performance.

Niroshan kicks off his presentation by stating that it’s important to identify users across the multiple devices that we have today and relate any online and offline activites such as when users search for products online on a website and purchase the product offline, and also that it’s important to identify advanced user segments.

He later moved onto talk about some features of universal analytics which are: measurement protocol which allows data from different users to be obtained and client/user ID’s which can be assigned to unique people (thankfully we don’t see personal information coming into play).

According to Niroshan, with universal analytics, when properly implemented we can view data in the perspective of the user not just per visit view as app analytics alone shows.

Niroshan and Dinesh now wrap up their stage and step off after a short Q&A session.


Niroshan Google Day Sri LankaIMG_0292

CPA in Adwords/Facebook Could Be Misleading

Google Adwords are being utilized by advertisers to assist in the marketing of their products and their businesses. Optimization of the campaign raises the markup value as well as conversion volume. The successful way of running a business online is to use KPIs to measure success. The main parts of KPIs are volume and markup balance in order to promote as much profit as possible.

A crucial metric within Adwords or any type of paid advertising platform to optimize an ad campaign is the CPA. Almost all advertisers lean towards the use of CPA to assist in optimizing their campaigns to promote the highest profitability available. Advertisers are beginning to consider the profitability of using a form of CPA to measure keyword levels in Adwords or Facebook, however, advanced analysis of channel profitability through Universal Analytics have found that CPA in Adwords could be misleading to the advertiser and lead to less profits in campaigns. With the usage of Universal Analytics, there is the possibility of linking the online and the offline world and measure much more accurately allowing it to calculate a true CPA. There are certain keywords that can lead customers to purchase extra services, or add-ons, such as upgrades to products that they have already purchased. Using certain keywords can assist in increasing your profits by distributing a comparatively larger budget to them.

Multi-channel reporting helps to identify if customers are using more than one channel to complete the conversion. By taking a closer look at the Facebook advertising campaign, advertisers can identify the CPA but actually they need to dig into the multi-channel reports to check the total channel path and the total cost of a customer. If a customer use Adwords PPC in their conversion path then the CPA will change. You need to add Facebook cost plus Adwords PPC cost to find the true CPA. In this case Facebook may not profitable as Facebook CPA report says.

Find the live example explanation with the presentation

Track Paypal Conversion (100%) with Google Universal Analytics with The Demography

Universal Analytics TrackingI had a problem in my head for a long time about Adowrds conversion and PayPal payments. Both companies aren’t going together to help business owner to track PayPal payment as a conversion in Google Adwords and Google Analytics. There are two cases in PayPal transactions that we are experiencing


Customer pays via PayPal and he needs to perform an action ( Eg- download a ebook or software)

  • You can attached the tracking code to the download page(or action page)

Customer pays via PayPal and leave the PayPal ( This happens when you are providing a service)

Paypal Tracking using Google Universal Analytics

  • No action page
  • Customer leave PayPal page after they see the PayPal thank you page
  • Difficult to track conversions

In the second case you can’t just track all the conversion from Google Analytics or Google Adwords so you have three options.

  1. Track signups as the conversion
  2. Track successful PayPal redirection as the conversion (In my experience it is below that the 10% but it may vary)
  3. Track click event on the buy now button that redirects to PayPal – not accurate

As my experience above methods aren’t  accurate for the business that I’m dealing with so I just wanted to discover a new method. Suddenly Google Universal Analytics came up with bunch of new features including “Measurement Protocol“. From this I say we can track 100% conversions with additional dimensions such as gender, PayPal transaction amount etc..

Let’s take a real life example to describe the situation

  1. customer reaches the web site
  2. register on the the site – collect name, email via a form
  3. Call before perform the purchase
  4. pay via PayPal, amount can be different
  5. close the PayPal before redirecting the thank you page
  6. Agent give the service and collect additional data

Now time to track 100% conversions

Collect CID (32 bit Client ID from Google Analytics) from each visitor and pass that ID to PayPal via the registration form. Once the payment is completed, fire an offline event with the value through measurement protocol using same CID.  GUA will link the previous user session to the conversion and now you have actual earnings for each keywords and for each channel with all the dimensions.

From this method you can track conversions without any problem and definitely you need a developer to do this for you. In this case we used, Google Analytic to track conversions but you can import those conversion to Google Adwords by linking them. But we have a problem here that is Google Analytics gives credit to last click. To avoid this we have two options in the GUA.

  1. Exclude subdomains and referees
  2. Exclude organic keywords

Other than this method you can use noverride, multi channel analysis and GA tweaks to find the actual Adwords keyword.