It was predicted that by the end of 2011 Global ad expenditure would be at US$464 billion, 3.5% higher than in 2010, and then accelerate to US$486 billion in 2012 – a 4.7% growth – according to predictions published in December 2011 by ZenithOPtimedia, a Publicis media agency.

Online ad expenditure will increase its share of the ad market from 15.9% in 2011 to 21.2% in 2014. The need for media channel attribution modelling is growing tremendously.

What you will get out of this post:

• How to identify consistent and cost-effective channels to produce revenue or brand awareness
• How to benefit from understanding the interactions of various channels
• How to determine the average time to purchase to look for improvement opportunities

1- Which channels produce results and which ones only produce traffic?

According to a survey conducted by Forrester on the Purchase path of online buyers in March 2011, nearly 50% of online transactions followed multiple exposures to web marketing efforts. Today marketers can follow a customer’s journey as they open branded email, click banners or paid search terms then continue on to order products or services. When done with proper scrutiny, this type of analytics provides marketers the opportunity to think beyond the traditional “last-click” measurement they typically attribute to marketing programs.
Of course, the first step is having a measurement tool that attributes sales to specific channels. For effective optimisation, you must be able to see the contribution that your different channels have on sales.

Once you can measure sales attribution, it’s time to begin optimising. A key point to agree upon is that a channel’s value is greatly affected by the quality of the marketing placed into it.

You want to make sure you are putting forward the best piece of marketing possible to give each channel its best opportunity to provide results. Work with your agency and solution provider partners on collecting benchmarking, keyword research and any other data relevant to your business and target audience segments.

2- Using Common Customer Paths to Optimise Channel Interaction

According to Forrester , “Fifty-seven percent of the interactive marketing professionals surveyed measure results for each channel, but less than half, only 28%, measure the influence of one channel on another”.

The problem with this “swim lane” approach to measuring channel effectiveness, is that consumers don’t interact with a brand or make buying decisions in straight swim lane style interactions. It’s also possible that a customer interacts with several channels before making a purchase.

Due to the fact that customers can often interact with several touch points before making their purchase, the traditional “last channel” approach to measuring contribution to conversion falls short.

Focusing only on attributing sales to the last channel can mask some of the hidden gems that truly drive sales. By creating a more advanced attribution analysis model, you may find that something, which is less expensive like non-branded search terms, actually accounts for most sequences that lead to a sale. Finding out that a lower cost channel is an important sales driver can be a great boost to your ROI.

For example, AT Internet’s Channel Optimizer allows users to see up to 15 channels in the sequences leading up to a sale and even gives users a detailed access report per order:

When you set out to optimise your spend on online channels, a good place to start is with the ones that contribute the most.

This may seem like a cumbersome task, but the cost savings that can be gained from recognising over attribution to expensive publishers, or over use of expensive marketing channels such as pay-per-click is worth the few extra man hours spent on doing the research.

Online intelligence, just like business intelligence, is an investment in streamlining your resources to achieve optimal results.

3 – Reduce the Delay between Channel Interaction and Purchase

Before the global adoption of exchanging money for goods and services online, marketers were constantly engaged in a battle to speed up a customer’s purchase cycle. Typcially the five stages are 1. Awareness 2. Information Search 3. Alternative Evaluation 4. Purchase Decision 5. Post-Purchase Behaviour.

The typical struggle was to speed up the cycle because if there was too much latency, especially between stages 2-4, it was increasingly likely that the sale was lost. Even in today’s 4G high-speed way with my iPhone society, marketers indeed continue to aspire to reduce the time between their advertisement and its intended purpose of creating a sale.

Luckily, with the proliferation of web analytics, data is now available to see the duration between a customer’s first interaction with your ad and the completion of an order. By using this information it’s possible to take action on channels that aren’t moving your customer through the purchase cycle.

As an example, combining data from AT Internet’s Sales Tracker and ChannelOptimizer Tools will give you the insight necessary to begin building an analysis model to help understand your customers’ purchase cycle.

By pairing up order and access details it’s possible to see the channels accessed, the duration between those access points, whether or not the user is a returning customer and other order details. Once paired up and placed into a spreadsheet you can begin to understand the average latency periods of different types of customers.

Following through with this advanced use of the data, you might see something like the fact that average durations between channel interaction and purchase go down after an influential blogger writes a post about your industry or product. With this information you can schedule your ad buys more effectively when you know that your customers are more likely to be closer to the purchase stage of their purchase cycle.

Partnering with solution provider’s like AT Internet you are able to request custom reports to be built to really get the most out of your data. Also with our growing list of online marketing partnerships AT Internet allows you to have increased convergence of your online marketing data.

Written by Michael Nemirovski and Carole Pero