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How Can You Use Technology To Improve Marketing Decisions for Superior Customer Acquisition?

Introduction

The acquisition of new customers is an important function for most businesses as it represents the primary method of generating healthy and sustainable growth. One of the major opportunities for using technology in this ongoing process is the ability to both collect data and manage it more effectively than was previously possible. This enables more precise segmentation, targeting and response measurement as well as faster feedback on the all important ROI obtained from a campaign.

Historical perspective

Prior to the use of customer acquisition technologies and techniques like data mining, personalisation, or CRM, a marketer would use their expertise and knowledge of existing customers to identify a new segment of the market that they believed to offer potential for customer acquisition. Having profiled this group in terms of demographic, in the case of direct mail, a broker or service bureau would be used to obtain lists of those meeting the required criteria.

The key issue with this method is that is lacks precision. The classification of customers into groups that have similar demographics to the target is traditionally based on assumptions about purchasing activity. In other words, it depends on the ability of the marketer to ‘know’ their customers very well.

If handled by an experienced marketer with plenty of exposure to the target market, the campaign is often highly effective. For sustained customer acquisition, however, this approach is inadequate for these reasons:

• It is too dependent on the skills and expertise of individuals (who will eventually leave the company).
• As the quantity of customers that a business needs to acquire increases, so the segments and behavioural predictions become more difficult to work out.
• The standard lists of prospects that a marketer can obtain tend to be fairly basic. Apart from the subject classification (e.g. ‘IT managers in medium sized companies’) the list data often may only include contact information.

The traditional approach – without technology does not enable a marketer to break apart their lists and score or profile potential customers.

How technology can help

A key benefit of technologies like databases is their ability to speed up or automate processes that would typically be highly labour intensive. In particular, this means collection of data and being able to correlate and combine data from numerous different sources to provide insight that would not have previously existed. In other words, it is an enabler for the creative talent of a superior marketer who has a hunch about a great way to acquire new customers and needs to be able to test their theory and drill down into the prospect list to see who and how many genuinely justify the expenditure of a campaign.

Defining acquisition criteria

Another crucial factor in determining the success of new technologies in the customer acquisition process is how well organised and segmented not only their list is, but also the responses from prospects – their interactions with the business when a campaign is started.

It is important to define the objectives of a marketing campaign and to rationalise these into types of behaviour so they can be more easily analysed by a system. The responses may include yes/no or categorical options. For example, did the customer contact the call centre in response to our campaign? (yes/no) or what type of merchandise did the customer express an interest in? (categorical).

By correlating responses with product catalogue data or other classification systems it is possible to align marketing data with other areas of the business such as sales, production and finance. This enables a marketer to develop a view of the customer that is more holistic and truly reflective of their interactions with the business.

As well as the type of responses, the other crucial distinction to help evaluate the ROI from a given campaign is whether they can be classified as positive or negative. Within these definitions, there are also further categorisations. For example, an obvious positive reaction to a e-mail campaign is that the prospect asked for more information, but this will typically be the first phase in the sales process, just because they have enquired does not mean they will buy. Having adequate systems in place to store the point where a prospect responded negatively is crucial to subsequent optimisation of a campaign.

The importance of data

One of the key benefits of data mining technology is the ability to create predictive models. With existing customers, the business may already have a wealth of detail already collected that can be used to predict likely behavioural patterns. With acquisition campaigns, this is usually not possible as the amount of third party data available is restricted to contact details. The solution is to find a relationship between the information that you do have and the behaviour to be modelled.

Starting with the prospect list, you will know some basic information about each target prospect which can be used to help refine the data mining methods used. For example, in the case of a furniture manufacturer, if you have a database of new homeowners that consists of just name and address, this can be matched by postcode against a database of existing customers to isolate potential purchasing trends. Taking a more complex route, if there has been a substantial increase in house prices in one postcode it is possible that new homeowners will be more interested in financing for their purchase as one would assume they have less funds available, so to these prospects, offers involving interest free credit deals might be favourably received. By overlaying one database over the top of another, it is possible to gain greater insight and so efficiently allocate them to very tightly defined market segments.

Implementing these kind of comparative activities on a large scale without data mining technology is complex, time consuming and expensive.

Testing campaigns using technology

Having carried out the analysis to develop a predictive model, it is necessary to test it. Where internet technology can offer benefits is the ease with which is it possible to test and refine models with minimal work required.

In the case of direct mail campaigns, for example, to run a test it is still necessary to actually print and distribute marketing collateral and have call centres in place along with formal tracking systems. With e-mail marketing, however, it is possible to radically shorten the duration between prospect identification and actually releasing the campaign live. The costs advantage of this method is also substantial.

Online customer acquisition

The ability to set up online campaigns so quickly and easily has lead to some blurring of the lines between acquisition campaigns and market research. A technique often espoused by Google AdWords consultants is to use search marketing prior to even producing a product or offering a service. Within ten minutes it is possible to release a series of campaigns targeted at different segments and start monitoring results that indicate potential levels of demand.

The key benefit of on-line customer acquisition is the ability to collect copious quantities of data about customer behaviour and potential purchasing activity. This can be carried out from the point at which the prospect enters a site up to the point they make an enquiry and identify themselves. This gives marketing managers the ability to compare pre and post enquiry data to further refine their predictive models.

Conclusion

That technology can help marketers make the right decisions to support their customer acquisition campaigns is not in doubt, however, there are a several key principles that must be observed to ensure that the investment into them is not wasteful.

Technology is suited to the scientific or mechanical elements of marketing campaigns such as:

• Carrying out repetitive or laborious work
• Large scale data processing
• Tracking and carrying out routine surveillance of prospects
• Modelling predictive behaviour

The ‘art’ of marketing is crafting compelling offers to prospects and being able to identify a segment of the market that is a) not saturated with competitors and b) offers the possibility to sell higher margin goods and services. Technology is unlikely to replace these skills for the foreseeable future.

Ralph Windsor is a senior partner in Daydream, developers of digital asset management software and solutions, established since 1995. He has fourteen years experience of delivering marketing technology solutions acquired as a developer, project manager and digital asset management consultant working with clients such as Major League Baseball, WS Atkins, Credit Suisse and UNISON.

To find out more about Daydream and our services e-mail: info@daydream.co.uk or telephone us on +44 (0)20 7096 1471.

 

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