Your SlideShare is downloading. ×
  • Like

Thanks for flagging this SlideShare!

Oops! An error has occurred.

×

Now you can save presentations on your phone or tablet

Available for both IPhone and Android

Text the download link to your phone

Standard text messaging rates apply

Going Beyond Retargeting: A 3-Step Targeting Strategy To Identify Customers Along The Buying Life Cycle As Demonstrated By A Real Case Study

  • 346 views
Published

Retargeting is one of the most commonly used marketing tactics as it is able to bring back the 98% of site visitors who leave without converting. Retargeting works by keeping track of people who visit …

Retargeting is one of the most commonly used marketing tactics as it is able to bring back the 98% of site visitors who leave without converting. Retargeting works by keeping track of people who visit your site and displaying your retargeting ads to them as they visit other sites online. The beauty to this technology is that it is only serving ads to people who have shown at least some amount of engagement in your brand. This makes retargeting a smarter spend than most other display ad campaigns as it focuses on your brand’s engaged user. However, retargeting alone often end up a smaller size of target audience pool, meaning less traffic and sales opportunities.

In this real case study, we will demonstrate how the use of the different data together with the targeting techniques can assist the different stages along a business’ customer buying cycle.

Published in Technology , Business
  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
    Be the first to comment
    Be the first to like this
No Downloads

Views

Total Views
346
On SlideShare
0
From Embeds
0
Number of Embeds
0

Actions

Shares
Downloads
21
Comments
0
Likes
0

Embeds 0

No embeds

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
    No notes for slide

Transcript

  • 1. Going Beyond Retargeting A 3-Step Targeting Strategy To Identify Customers Along The Buying Life Cycle As Demonstrated By A Real Case Study
  • 2. Introduction Retargeting is one of the most commonly used marketing tactics as it is able to bring back the 98% of site visitors who leave without converting. Retargeting works by keeping track of people who visit your site and displaying your retargeting ads to them as they visit other sites online. The beauty to this technology is that it is only serving ads to people who have shown at least some amount of engagement in your brand. This makes retargeting a smarter spend than most other display ad campaigns as it focuses on your brand’s engaged user. However, retargeting alone often end up a smaller size of target audience pool, meaning less traffic and sales opportunities. Thanks to the advancement of technology in recent years, marketers are now having more options to extract greater value from retargeting by leveraging big data and other targeting techniques. In this paper, we will discuss how various techniques can work together along the sales funnel to eventually lift campaign ROI through a real case study. 1
  • 3. The Basis of Targeting is Data Online targeting works at its best only when it is supported by sufficient and relevant data. The data-pyramid divides the Onsite Customer Data commonly available data into 4 layers. The bottom of the pyramid is the placement data which refers to the information about a specific ad placement and its ad performance over time, e.g. size and location of placement, average CTR from historical data, viewable impression, etc. Moving up the data-pyramid is the audience segment data. Search Intent Data CTR and Conversion Rate Audience Segment Data There are now data providers who are able to collect comprehensive information about users’ interests and intents through their online and offline behaviors and activities. These non-personally identifiable information is clustered into segments, creating exact audience groups that can help marketers to reach anywhere online. The use of audience Placement Data Area = Volume of Data Available segment data offers a higher level of targeting precision than merely relying on placement data since it provides insight on the audience’s behavior and interest. Up one level is the search intent data. Search retargeting is a prospecting tool which helps to identify people who are likely to convert because they have already searched for a term that matters to your business. Valuable data concerning the shopping intent behind the searchers can be extracted for marketers to re-target users with higher shopping intent, i.e. close to the bottom of the conversion funnel. At the top of the data-pyramid is the onsite customer data which refers to all audience data collected via the activities the users conducted in the marketer’s sites, such as the pages the user has visited, the information downloaded and items added to the shopping cart. Onsite users have already checked out the brand and have some familiarity with the company. Data from each of the 4 layers has their own values to help an effective targeting strategy. For instance, placement data is usually what every marketer will first look into when planning for a campaign since they are the most readily available in most ad planning tools and ad exchanges. But marketers will also look for data beyond contextual/placement level that can show audience behavior and intent for more precise targeting. Therefore, the 4 layers of data complement with each other, and in fact, they should be employed together to form a comprehensive strategy to strengthen the different stages of the customer buying funnel. The following is a real case study to demonstrate how the use of the different data together with the targeting techniques can assist the different stages along a business’ customer buying cycle. 2
  • 4. Case Study Background: Our client, one of the China’s most popular shopping sites, aims to lift ROI and the number of online purchase. Challenge: The client has used onsite retargeting and generated a satisfactory ROI. However, the number of conversions from retargeting is diminishing over time. Stage 1: Onsite Retargeting Many marketers share the same experience of seeing the Site Traffic number of conversions brought by onsite retargeting as often being very limited . In fact it could be due to improper tagging of the web pages. Usually, those visitors marketers select for retargeting are the ones who have Front Page visited the page towards the end of the conversion funnel, for example the shopping cart page. In fact, to get the most out of onsite retargeting, marketers should establish Marketers who set up retargeting tag only towards the end of the customer funnel will limit the number of relevant audience to get exposed to the retargeting ad. Product Page a better visitor segmentation based not only on the page the visitor has visited, but to also consider the behavior of Shopping Cart the visitors. Instead of retargeting only the visitors who made purchases or those who left the shopping cart without making a purchase, our client has segmented visitors according to their onsite browsing behavior as follows: 87,835 16,589 visitors who have visited at least the homepage visitors who have downloaded coupons Visitors with brand awareness = 165,359 unique visitors Visitors with purchase intent 44,783 43,234 visitors who have visited any of the product page visitors who have visited made a purchase Visitors interested in products Repeat Customers With the new visitor segmentations, the client has significantly expanded the base of audiences for retargeting. In less than 2 weeks, the effect of retargeting has kicked in: New Visitors Old Visitors Conversions CPA Conversions CPA Before 324 $71 81 $233 After 465 $63 89 $211 Up 44% Down 11% Up 10% Down 9% The new approach in visitor segmentation has lifted conversions from old visitors by as much as 44% 3
  • 5. Stage 2: Target Search Audience + Pre-packaged Audience Segment While retargeting is effective in bringing prior visitors back to the website to increase the chance of repeat purchase, marketers should also consider broadening the number of visitors in the upper part of the conversion funnel so it could create a continual supply of new visitors to the website. In this case, the client has added audience segments who have previously searched keywords related to the products, and also leveraged pre-packaged audience segments that have shown similar online behavior and browsing patterns to its existing site visitors. Influx of new site visitors Stage 2 Increase traffic to create influx of visitors by targeting to users that show relevant search intent and also leverage pre-packaged audience segments Front Page Stage 1 Onsite Optimization Product Page Shopping Cart Online Purchase New Visitors Old Visitors Conversions CPA $63 89 $211 $48 315 $150 Down 24% Up 254% Down 29% Conversions CPA Before 465 After 588 Up 26% The use of search retargeting and pre-packaged audience segments created a strong prospecting effect which generates a much higher traffic from new visitors. 4
  • 6. Stage 3: Add even more new customers to the top of the buying funnel by Machine Learning Machine learning is a powerful tool to help marketers identify users who exhibit similar behavioral pattern to your existing online customers. In the case of this client, XMO’s machine learning takes place by analyzing the patterns of client’s users who have made purchases online and identified a segment of relevant audience of around 2.3 million online users in 1 week. By reaching the users identified earlier and also the new users identified via machine learning, the result was: New Visitors Old Visitors Conversions CPA Conversions CPA Before 588 $48 315 $150 After 624 $42 397 $171 Up 6% Down 13% Up 26% Up 14% Machine leaning is able to recongnize the behavioral traits of your existing visitors and then identify new visitors from the vast sea of online inventories who are likely to exhibit the same pattern, enable you to prospect relevant users in a more targeted approach. Despite a slight surge in the cost-per-acquisition, it can be seen that machine learning can effectively boost the number of conversions by bringing more new visitors to the site. Q What is Machine Learning? A From Wikipedia: Machine learning is a branch of artificial intelligence concerned with the design and development of algorithms that take as input empirical data and yield patterns or predictions thought to be features of the underlying mechanism that generated the data. A learner can take advantage of examples (data) to capture characteristics of interest of their unknown underlying probability distribution. A major focus of machine learning research is the design of algorithms that recognize complex patterns and make intelligent decisions based on input data. 5
  • 7. Key Takeaways The use of various data can assist marketers to improve No. of Online Audience campaign performance in 2 folds. Firstly, it increases the base of the targeted audience pool allowing marketer to Onsite data to retarget users who have visited to the site have a continual supply of new traffic running to the site. Secondly, it strengthens the different parts along the customer buying funnel. Marketers usually adopt Leverage search data to enhance the reach of relevant users who have shown interest to the product. retargeting hoping to bring “shopping cart-abandoners” and existing customers back. In fact, for the business to The use of 3rd party pre-packaged audience segments to broaden the reach further to large base of online audience who have not visited the site before. grow in a sustainable manner, marketers should also concern themselves with the split between existing and Use machine leaming to automatically learn the behavioral traits of your existing users and identify new users who exhibit the same pattern. new customers who are generating sales for the business. The use of data from search intent, prepackaged audience group and machine learning would help to generate more customers at the top of the funnel. Together with the right creative and messaging strategy in place, it helps to accelerate customers to move along the conversion funnel and create a huge business opportunity for the business. The use of data from search intent, pre-packaged audience segment and machine learning can help to generate more customers to enter the top of the funnel. Awareness Interest Decision Shopping Cart Most marketers adopt retargeting to only catch the customers who have previously reached towards the end of the buying funnel. Customers About iClick Redefine the digital marketplace and advertising performance with data, insights and innovations. iClick is the first online buy-side platform in Asia. With its proprietary cross-marketplace optimization platform - XMO, iClick helps marketers adapt to the complex advertising ecosystem by simplifying and automating the online marketing process. This cutting-edge data technology brings efficiency to campaigns and eventually maximizes ROI in a sustainable manner. Visit us at www.i-click.asia or follow our weibo www.weibo.com/iclickasia Sales contact: sales@i-click.asia 6