Optimisation

This article, written by Neil Mason, was originally published on Clickz.com and is republished here with permission.

In this series of articles I am looking at the subject of digital marketing optimisation. At its core optimisation is a combination of philosophy, process, data and technology. You have to want to optimise and you have to be able to go through the “test, learn and adjust” cycles quickly enough to make a difference. Last time I outlined the approach to breaking down the digital marketing process into its main components of acquisition, conversion and retention and looking at the optimisation challenges within each of these areas. This week I look a deeper look at the first of these processes: acquisition.

Campaign optimisation is probably the most established optimisation practice. Acquisition marketing has been the corner stone of digital marketing for many years and a number of us can probably remember the mantra of the dot-com days when all the focus was on “eyeballs” and getting as many of them to the site as possible, often with little regards to what happened when they got there. Things have moved on a bit since then. Thankfully we now take a more sophisticated approach to measuring and optimising our acquisition marketing efforts. However, I think that there is still a way to go as campaign optimisation is a multi-level problem and once you have cracked one level then it’s time to move on to the next.

I think campaign optimisation operates on three levels:

• In-channel optimisation
• Cross-channel optimisation
• Multi-channel optimisation

In-channel optimisation

This is the process of optimisation within a single digital marketing channel (ie PPC search, display advertising etc) and is in effect what we have been doing for years. Over that time we have become more sophisticated and we have seen the development of solid processes and the deployment of analytics and technology to help automate the optimisation processes. Within PPC search for example, there have been bid management tools around for years and a whole industry discipline has grown up around the optimisation of PPC and organic search marketing activity.

We have also seen the technology evolve to the extent where campaigns can be optimised in almost real time through automated algorithmic approaches like of SearchRev in the case of PPC marketing or DART Adapt for display advertising. We’re almost at the point of “fire and forget” where once the initial deployment has been made and the system is calibrated, little manual intervention is really required.

That’s all great, as long as you are optimising against the tight thing and that you’re correctly attributing value to the right behaviours. A good case in point again is PPC search marketing. Classically PPC optimisation is done at the keyword level looking at the clicks that generated the conversions and adjusting bid-management strategies accordingly. However, we know that in a lot of cases it takes multiple touch points to generate a conversion, and so value needs to be attributed all along the acquisition value chain rather than just against what happened at the end.

Cross-channel optimisation

“In-channel” optimisation is relatively straightforward. It usually involves a single piece of technology and the data to drive the optimisation process is generally sitting in one place. The problem is that marketers rarely market using a single digital channel. They use a combination of different channels often at the same time to achieve their goals. Display advertising may be used for generating awareness; search marketing may be used for generating response and so on. Each of these channels might be optimised in their own right but what about the impacts of one digital channel on another?

A classic example of this was when one of my clients went through a process of optimising their search marketing and display marketing independently from each other. They came to the conclusion that their display advertising wasn’t working hard enough for them, whereas their search marketing was. They switched investment out of display marketing into more search marketing and then promptly saw their search volumes drop. Up until this point they hadn’t appreciated how much display advertising was driving search volumes because they were optimising within the channel and in the case of display they were optimising against the wrong thing. They hurriedly reverted to their previous approach and saw search volumes recover. But they were none the wiser. They knew there’s a relationship between search and display (and their other channels) but they didn’t know how to optimise it and that was because their data was all over the place.

The key to cross-channel optimisation is data integration. It’s necessary to have the different channels activity and responses in the same database. This might be achieved by using a single campaign management system, by deploying a universal tag or by integrating the data in a separate system. Either way, once the data is in the same database, it’s possible to look at the effect of different channels on each other and on conversions and then to be able to optimise accordingly.

Multi-channel optimisation

Increasingly digital or online marketing doesn’t sit in glorious isolation from an organisation’s other marketing efforts. It’s a multi-channel world and businesses are looking to integrate their online and offline marketing strategies and tactics. So the problem becomes broader. It’s not just about how do I optimise my search marketing, or how do I manage all my digital channels, it’s about how do I optimise the total marketing mix? Online and offline? Search, display, TC, radio, print – the lot? This is the strategic marketing optimisation problem that companies are beginning to wrestle with. Again one of the main challenges is data integration.

Online and offline marketing data generally have quite different characteristics which means that it’s not necessarily easy to integrate them. Online marketing data is usually at the cookie level, tracking an individual user (or more precisely, an individual device). Offline marketing data is usually at the “market” level ie starting at a country or a regional level and down to individual stations, publications and so on. User level data and market level data can be difficult to marry up and relate to each other. With the development of geographical profiling from IP addresses it is getting easier but the analysis techniques will then also be different and are more likely to resemble the inferential modelling techniques of offline marketing rather than the “direct cause and effect” techniques used in the online world.

So, campaign optimisation is a multi-tiered problem. It’s like going on a hike up a mountain. When you get to the top of one summit, another one comes into view and on you go. If you’ve just about got your search engine marketing cracked, it’s time to move on to the next problem!

Next time I’ll be taking a look at conversion optimisation. Till then…

This article, written by Neil Mason, was originally published on Clickz.com and is republished here with permission.

In my last column I looked at the concept of “data driven marketing” and outlined what I believe to be the for key components for successful data driven marketing, namely: Philosophy, Processes, Data and Technology.

At its heart data driven marketing underpins the drive towards optimisation but optimisation is one of those words that’s used a lot but often means different things to different people. A bit like segmentation, engagement and so on. So in this series of columns I thought I would offer my take on optimisation, what is means and how it can be achieved.

I first came across “optimisation” as part of my college degree course. It was presented as a mathematical problem; how do I maximise a desired outcome given a set of certain constraints? This is the way I have tended to think about optimisation ever since, particularly when it comes to marketing optimisation. My desired outcome will be things like orders, revenue or profit and my constraints will be things like money, time and resources. The challenge is to maximise the return on investment in marketing.

The problem with this purely mathematical approach to optimisation is that often the problem is too large or complex to solve easily. You need to understand and define the relationship between all the variables (such as sales and advertising) and then use the mathematics to determine the optimal allocation across the various inputs. The challenge is that there are often too many variables and the relationships are too complex to be solved easily. The approach then is to chunk the problem down and iterate towards a solution. This is where the components of data driven marketing come into play.

In the digital world the ultimate goal of many marketers is to maximise customer lifetime value and to allocate the resources available in such a way to achieve that. The issue is that things like customer lifetime value can be difficult to define and to measure and marketers may not have the ability to efficiently manage all the resources appropriately. The intent may be there but the ability to execute may not. As a result we break the overall process into smaller processes and we need to begin to think about how we can optimise individual separate processes rather than the complete value chain in one go.

We already think about digital marketing as three separate processes, namely:

• Acquisition
• Conversion
• Retention

Sometimes these processes can be too separated with little joined up thinking between the three. Having said that, for the purposes of optimisation and given the constraints of data and technology, it probably makes sense still to use them separately as the basis for our optimisation strategy. However, it is useful to bear in mind that what we are trying to so ultimately is to maximise the allocation of resources and investment across the whole customer lifecycle.

So what problems are we trying to solve? In acquisition we are trying to optimise our campaigns to increase the propensity of people to visit a website and engage. This is an area where there has been a lot of focus over the years and where technology has made a significant impact in either allowing marketers to iterate through the cycles more quickly or where the technology effectively automated the optimisation process. However, I think that the goalposts are moving and the problem set is changing and increasingly marketers need to be looking to optimise in a different way.

When it comes to conversion what we are trying to do is to increase the likelihood of some desired outcomes, whether that is an order, a registration and download or telephone call. Here there has been a lot more attention given over the past couple of years and where analytical technology has evolved to help marketers understand how to improve site architecture and design. There is more work to be done in this area though and the technologies and the processes to manage them need to be more widely adopted.

With retention marketing what we are looking to do is to increase customer value. Here we are talking about maximising on the investments that have already been made in acquisition and conversion so that we don’t have to make those investments again. With a few notable exceptions I don’t think that many organisations are focused on this area at the moment.

Over the next few columns I’ll take a look at optimisation is more detail, looking at acquisition, conversion and retention and examining the philosophy, processes required and data and techniques available to maximise the effectiveness these individual processes. Till then…

This article, written by Neil Mason, was originally published on Clickz.com and is republished here with permission.

I was recently asked to put together a workshop session on “Data driven marketing” for a class of digital marketing students. Part of what I asked to talk about to explain what data driven marketing is and how to go about it. In pulling the material together for the workshop I came to the conclusion that there are four key components for successful data driven marketing, some of which are obvious and some perhaps less so.

The four components are:

• Philosophy
• Processes
• Data
• Technology

Philosophy

This is the most important component I believe. To be successful at data driven marketing, an organisation needs to have the right culture and philosophy. At its hear t, data driven marketing is about continuous optimisation and iterative improvement. It’s the deployment of a “test, learn and adjust” philosophy. However, you can have the best data and technology in the world (see later) but if there is not the desire to act and to change, then the data and technology are only providing interest as opposed to insight. Organisations must have the “desire to act”.

At a Web Analytics Wednesday I attended in Berlin last week a lot of the talk in the networking session was not about metrics and systems but about how do you embed analytics within organisations? The biggest challenge often facing analysts is getting support for the development of their programmes because culturally the organisation doesn’t have a philosophy of measurement and accountability.

Processes

If “philosophy” is about the desire to act, then “processes” is about the ability to act. More specifically it’s about the ability to execute and then to react. These processes involve the management of the technologies and also the management of the decision making. Processes will include building “measurement” into the marketing development process for example, so that there is no question that new campaign won’t be tracked properly or that new content on the website won’t be tagged. It also involves ensuring that a feedback mechanism is in place that enables trends to be identified and changes to be made in the appropriate timescales.

One example I had in the past demonstrated to me where a potential desire to act was inhibited by an inability to execute. We did a piece of segmentation analysis for a retailer to feed into their email marketing programme. In the analysis we identified a number of distinct groups of customer with different purchasing behaviour that could be marketed to in a more customised way. We also identified some key timing mechanisms that could potentially double the customer’s propensity to buy again. Despite this insights the segments were never deployed operationally because the retailer didn’t have the resources and processes in place to develop and deliver more targeted email marketing programmes.

Data

Data is of course a vital ingredient in the mix, but it is the organisational culture and processes that provide the recipe for success. Good quality data is important and attention must be paid to getting the numbers right. People are reluctant to make decisions if they don’t have any faith in the data.

Also data driven marketing needs integrated data rather than data sitting in silos. Often within organisations different types of data sit in databases and different functions may have ownership of different data. For data driven marketing activities to be effective, the different data sources need to relate to each other. To understand and optimise marketing across channels, the data from different channels (PPC search, display ads, email etc) needs to be in the same place, whether that be in a web analytics systems, a campaign management system or both. In addition data needs to be managed across the life cycle of the customer, for example by ensuing that data on how customers are acquired can be analysed with the customers’ long term value or profitability.

Technology

Finally the technology is the enabling component. It is the technology that allows you to execute and react either over the duration of a planning cycle or even in real time. I don’t think that technology can make up for deficiencies in the philosophy and processes, though if you have the right apporach and procedures, you can make progress even if your technology is not the most effective. Good technology enables you to cycle through the processes faster to the point where real time optimisation is possible. Like the data, the technologies should be integrated and allow the loop to be closed between insight and action.

So, the core ingredient of data driven marketing is good quality, integrated data. The technologies are the tools but it is the combination of the organisational philosophy and strong processes that will provide the recipe for success.