by James Lawson.

Marketing optimisation is an attractive concept: use predictive modelling and business rules to work out exactly which combinations of contacts, products and offers the direct marketing budget should be spent on. But optimisation tools tend to be costly and have historically been applied to improve the performance of high-volume direct mailing. With postal mail far less prominent today, are these tools still relevant and capable of improving today’s broad mix of offline and online channels?

Helping to plan

“If you can measure the outcome, then all channels can be optimised – online or offline,” says Mike Fisher, Chief Futurist at Indicia. “Typical optimisation solutions are designed to operate in a single channel marketing environment, and in general are able to deliver what is asked of them. However, once you introduce other channels, most solutions are not as qualified.”

Marketing optimisation takes the principles of target marketing - right customer, right offer, right time – and applies them to all a company’s customers, products and campaigns to find the optimum outbound mix of contacts and offers. Rather than finding the best individual for a predetermined campaign – the conventional method – optimisation tools work out how a particular customer (or perhaps segment) should be approached: via which channels, how often and with which offers.  The critical part is that the software does this within specified constraints, be that budget, channel capacity, maximum number of contacts per customer per month and so forth.

Each set of constraints forms a “scenario” and companies typically work through and rerun various scenarios until they have a solution that suits. Optimising solely for profit might suggest tripling the marketing budget to achieve the maximum possible returns while optimising within a fixed budget and perhaps setting a maximum response volume (for example at a call centre) would produce a completely different, smaller set of suggested contacts. On the basis of the results, marketers can then plan out their year’s campaigns and allocate budget roughly as required.

To come up with these figures, complex business rules and multiple propensity models are typically combined by custom software to predict how each customer or segment might respond, and so produce an optimum strategy set within defined constraints. Much other historical data is required, such as how response through a channel varies as outbound volume increases. It tends to be a technique that only companies with a clean, well-populated database and a good store of historical response information can adopt.

“Combining the data is the hardest part and we need to make this easier for customers,” says Peter Hardingham, Customer Engagement Modelling director at G2. “However, you can work with a partial view and still make good decisions.”

Historically, optimisation has been used with direct channels like the telephone and direct mail. With the rise of email and the web, the situation looks somewhat different. Though outbound email is very suitable for optimisation, its low cost delivery takes away much of direct mail’s justification for investment in optimisation, that is, reducing mailing costs while maintaining and increasing response. However there is a strong case for predictive modelling for email to avoid overcontact as well as to select the most attractive offers and creative treatments.

“Email is easiest for us to optimise while broadcast and social media channels are much more opaque,” says Andrew Campbell, Managing Director, Insight, 20:20 Dialogue. “The ones that are easy to track and predict response on are easy to optimise.”

Attributing response or sales uplift is essential to make use of optimisation and doing this for broadcast media such as TV and radio or channels such as field sales has always involved a certain amount of educated guesswork. The recently-arrived social media channels are similar: it’s tough enough to measure ROI on them directly, let alone predict what ROI will be and therefore what budget should be allocated to them in the year ahead.

“Social media is unmeasurable and unaccountable yet huge sums of money are being spent on it,” says Neil Johnson, planning director at dbg. “It can be useful to monitor it to see if a campaign is taking off, like ‘social media share of voice’, but I’m loath to use it as a standard KPI to assess campaign success.”

Even in direct channels, it’s often impossible to know which of the seven contacts a customer experienced was the one that made him or her go out and buy the product. Was it the mailing, the emails or the final phone call?

“It’s increasingly difficult to resolve and spot response, particularly when it’s a high value purchase,” explains Nigel Magson, managing director of Tangible Data. “You might base your optimisation on faulty response data.”

Without some accuracy in attribution, cross-channel optimisation starts to become dangerously inaccurate. Accuracy can only come from populating and linking response data from all channels at individual level on a single-customer-view database. Not a trivial task.

“It’s important to understand the different dynamics of online – what am I measuring – for Facebook it could be ‘fans’ or tweets via Twitter,” says Fisher. “Even these softer measures will need to be referenced back to ROI to ensure we can compare channel performance, because that is the objective – what is the best channel to use for that customer, and what is the impact on my ROI.”

The speed and interactivity of web and email also differentiates them from conventional channels and, as the web gives access to unheard-of levels of product information, user-generated reviews, price comparisons and so on, buyers are increasingly taking control of the purchase process themselves rather than simply responding to offers.

“The biggest trend now is to react to consumers rather than to predict their behaviour and send outbound messages,” says Campbell. “The programmes we are seeing understand the mechanisms in the customer journey and set up systems to respond quickly and appropriately rather than organising complex outbound campaigns.”

He notes that his company has to take a “top down” approach, allocating budget to online analysis, systems and other work so that clients can map the customer journey then discern the optimum actions to take at various critical points within it. Outbound campaigns get their own part of the budget and his company then optimises the targeting and creative within this constraint. However, others think today’s landscape has changed so much that planning a year in advance simply means missing opportunities.

Johnson dismisses the “old fixations with purchase timings and renewal cycles”, for example mailings targeted using insurance renewal dates. As prospective buyers now have instant access to information via the web, like Campbell he argues that effective sales and marketing is now far more about understanding customer behaviour and reacting quickly than outbound targeting.

“You can’t predict accurately months in advance what you are going to do,” he says, noting however that historical data is still essential to build understanding of customer behaviour. “You still rely on past data to predict the future but you have to monitor and optimise as you go along.”

He gives the example of Greenpeace’s very successful 2010 campaign against the deforestation caused by palm oil development. Social media was instrumental in quickly building momentum and, via petition sign-ups, also served to collect valuable supporter data that underpinned outbound calls soliciting membership subscription sales.

“Was there a model powering that? I doubt it,” says Johnson. “You’ll miss those opportunities if you plan all your activity a year ahead.”

However, a short-term, ad hoc approach would seem to make it extremely tough if not impossible for marketing directors to budget for the coming year ahead.

“You simply have to have a strategy going forward, so you do have to predict,” argues Hardingham. “Results-driven organisations need to plan 6 to 12 to 18 months out. Of course you are going to move that around but you have to know roughly what your targets are.”

There’s no doubt that the need to use modelling and other software tools to optimise contact strategy for direct channels is now widely accepted. Optimisation is a big step beyond that and is certainly happening, though only the biggest and most sophisticated businesses like Adobe are attempting to put it into practice.

At European telecoms business KPN, the company started to apply cross-campaign and cross-channel optimisation techniques using SPSS tools. Amongst other discoveries, the company found that it wasn’t contacting some of its best customers sufficiently often. According to the model, increasing contact frequency from three to four times within a six-month period would see KPN’s income from the top segment of customers actually increase by between 50 and 70 percent. Increasing contacts from four to five would have a similar effect.

“We have seen some big results with cross-campaign optimisation,” says Colin Shearer, Senior Vice President, Strategic Analytics at SPSS-IBM. “It’s now possible to get this technology in forms and packages that don’t cost a lot, so you can gain the benefits without huge investment.”

However when it comes to planning, the vast majority of UK marketers still employ spreadsheets or “back-of-a-fag-packet” techniques perhaps best left back in the 80s.

“I don’t see any use of automation for marketing planning,” says Magson. “It’s still done with lots of spreadsheets and any segmentation is usually done within each channel rather than across channels.”

Optimisation software is available from a broader range of vendors today, with suppliers like Agillic and WPP’s Fabric joining the likes of The Customer Partnership, IBM, Experian and Alterian. Other marketing analytics vendors are also adopting elements of the optimisation approach.

For example, Apteco’s PeopleStage campaign management tool can take response models built in its Discoverer module and then apply budgeting constraints during the selection stage. While not an optimisation tool as such, Tangible’s Magellan can take cost data at individual level and so generate key cost-related metrics at segment or campaign level across channels.

Optimisation can also be bought as a service from agencies; all the companies interviewed for this feature can offer consultancy on some flavour of direct channel optimisation.

Inbound or outbound?

Optimising multichannel outbound campaigns is certainly possible but its ROI will depend greatly on the mix of different channels concerned: the more predictable the response and income, the more useful optimisation techniques will be. Then there needs to be a good mix of products and services to select from. On top of that, there must be a top quality SCV in place, accurate cost and other data, plus the skills and infrastructure to make use of it.

Outbound volumes have also dropped dramatically, with the last decade’s carpet bombing giving way to smaller renewal and cross-selling campaigns, which also reduces optimisation’s appeal. Likewise, inbound targeting via the web and triggered email or via the call centre will also compete for funds. Every company will have to make its own choice.

“It’s not so much that certain channels are problematic, now it’s more about how you balance inbound and outbound work, and where you invest your budget,” concludes Shearer. “One of our clients only targets 6% of inbound customers but converts one in three of them.”