See - analytical database marketing on a budget!

GETTING STARTED WITH DATABASE ANALYSIS

Key to building and maintaining a relationship with your customers is the need to record and analyse all information that stems from that business relationship.

Assuming the first hurdle of bringing all relevant data together into a single customer view has been undertaken, then the next step is to correctly analyse your data, interpret the results and apply your findings to develop more appropriate and more highly targeted data-driven marketing strategies. These will deliver a host of benefits to your business including a greater return on your technology and marketing investment and a substantial increase in profitability.

SO, WHY ANALYSE YOUR DATA?

A marketing database would usually contain records of all your customers together with all of the transactions they have made with your organisation over time. This highly valuable resource would typically be enhanced with marketing, profile, survey, suppression and prospect data to provide you with the deepest customer understanding possible.

The saying that 'the whole is greater than the sum of the parts' is never truer than in database marketing, as when viewed in its entirety, this information will help to maximise the potential of your business and uncover otherwise hidden opportunities that will drive increased profitability. By using data mining and statistical analysis techniques, you will be able to better understand your customers and adapt your marketing to address both their needs and their behaviour.

However, customer analytics is not just a one-off exercise. To reap the rewards, data analysis needs to be carried out on an on-going basis to keep track of change and allow you to take the appropriate action on a timely and a proactive basis.

But to analyse your data effectively and reap the rewards, you need the right expertise, know-how and tools, plus of course reliable data.

CUSTOMER ANALYSIS - KEY BENEFITS

Targeting with precision is one of the major deliverables derived from increased customer knowledge. This will lead to increased profitability.

Informed customer investment

Knowing who are the more profitable and responsive customers to focus your marketing spend on will drive more sales at lower cost and hence increase marketing return on investment - ROI. For instance, rather than regularly selecting large blocks of customers that have purchased a specific product or service, you can segment these blocks on a number of factors including profitability and propensity to respond. Targeting these segments enables you to apportion your marketing spend more appropriately - more on the better prospects and less on those that may not add significant value to your bottom line.

More focused marketing

By segmenting your database it is possible to target your offerings to meet the needs and interests of your customers and prospects. You can examine survey responses and purchase or trading history, and group individuals sharing similar characteristics. These segments can then be marketed to by email, direct mail or telemarketing - using your data to: a) determine which is the more appropriate channel, and b) to analyse the effect of varying offer combinations and approaches.

Exploit cross sell and up-sell opportunities

Take a group of individuals who have purchased product X. Another who purchased product Y. And a third group that purchased product Z. Wouldn't you like to know how the profiles of each group compare with one another, and then how they compare to a fourth group of people who have purchased all three products. Data analysis will enable you to do this and then locate other individuals across your database that share the same profiles. Armed with this knowledge, you can target the prospects with a higher propensity to buy additional products (cross-sell). And, if you include their purchase values in your analysis, you will be able to use profiling to target those prospects more likely to increase the value of the purchases they make (up-sell).

New customer acquisition (recruitment)

Once you understand the characteristics of your most profitable and loyal customers, it is far easier for you to locate more of the same at the lowest possible cost. Consider that recruiting a new customer typically costs between five and twenty times the cost to retain one, and you will quickly see the sense in not only maintaining a loyalty strategy but also in targeting your acquisition campaigns towards prospects sharing similar profiles of your better customers.

Product development (bundles, offers, new products)

By really understanding your customers and the combinations of products they buy, in which order they buy them, how much they spend on their first, second and subsequent orders, when they buy, which types of offer makes them respond, where they show interest, etc., will enable you to put together more appropriate and probably more profitable product offerings. You can also develop and test new products or services that meet the needs of that particular group of customers and also create more appeal amongst other segments.

To grasp these benefits and apply your marketing investment more intelligently, necessitates not only the correctly derived analytical findings but also the right approach to turn them into marketing action. Otherwise the only result you will have to show for your analytical investment will be statistics and reports - no increased profits!

ANALYSIS STEPS

Understand the profiles and behaviour of your customers

This requires an examination of your customers by looking at the information you hold about each individual. You can also profile at a household or business level by rolling up the data from the individuals within each. Variables to examine should include lifetime value, spend patterns, product purchase patterns and behaviour, and attributes. Personal attributes could include: age, gender, lifestyle, leisure interests, occupation, income, accommodation type, geo-demographics... Company attributes could include: number of employees, turnover, type of business, job position, job responsibility... 

These variables need to be understood both individually and in terms of how they interact - affect and impact - upon one another. External data can be matched in to further increase your customer understanding, validate the information you hold and add additional dimensions to aid your targeting and help you really visualise who buys what, when, why, how and how often.

Segmentation

Once you understand your customer profiles you can use this and other database information to statistically segment individuals sharing similar characteristics. There are two main approaches to segmentation. The first uses techniques such as cluster analysis to create natural groups by measuring how closely attributes correlate. You can then examine the attributes for each group and describe them to paint a picture of your customer segment - average age 50, minimum age 45, maximum age 55, male, spend average £500 per year, etc.

The second approach to segmentation uses predictive modelling (such as regression analysis or neural networks) or response modelling (such as CHAID). These techniques can be used to identify which of your customers are most likely to respond to your offers, which generate higher levels of sales, who are more likely to result in bad debt, etc. The different types of customer can be related to recency, frequency and value of purchases, products or service purchased, payment method, offer, etc., plus their profile data. Clearly the actual variables used will be specific to your industry sector.

Usually modelling results in scores being derived - likelihood to buy, likelihood to respond, likelihood to lapse, likelihood to be your champion, etc. - and these stored against each customer record on your database. The scores are then used to group and rank individuals within segments and can also include other predictive factors such as future profitability, in total or by product.

Segmentation, predictive and response modelling will enable you to make informed marketing decisions to get more from your promotional spend and help prevent waste - in terms of both money and time - by not contacting people who are unlikely to respond to your offer.  And you will be able to invest appropriately in marketing to the individuals who are more likely to make repeat purchases.

Behaviour Analysis

Once you have profiled and segmented your customers, the next step is to look for change. This is more complex and requires a thorough understanding of statistical data analysis and often extensive computer processing in order to understand the dynamics of each of your customers and the segments they belong to - and yes an individual can belong to more than one segment! 

By comparing scores that are recalculated on a regular basis, it is possible to determine the significance in any change and then create new variables (fields) to contain suggested next-action indicators. These will help marketing staff determine who to contact, why and when. A clear benefit here is that if a customer who has been regularly spending £x per month suddenly reduces the amount or gradually slows their trading with you, this could indicate a likelihood that they will lapse. Knowing this before they do, enables you to contact them, understand the cause, calculate the effect and take appropriate action!

Marketing and Business Intelligence

There are may other analytical techniques including market research that can be used to increase your customer knowledge and better understand of your business, and by putting the two together you will be able to determine how best to both uncover and resolve problems. For example, you can pinpoint issues with fulfilment, slow delivery, poor product or service quality, bad customer interaction by call centre staff, etc., that if are not addressed will affect profitability, the loyalty of your customers and the overall success of your business. 

How to progress?

To successfully implement an analytical strategy you will need reliable data, the expertise and know-how, an understanding of the direct marketing channels in your industry sector, the supporting technologies and a way to apply the analysis findings to your marketing.  At Tech4T this is our focus. Look through our website and then contact us. We will have an appropriate solution to meet your needs - whether you want to undertake the analysis yourself in-house and need some support or software, out-source the work, or have a solution comprising of both.

See how Tech4T can help your data-driven marketing - click here

TechT's Customer Analysis Solutions - click here

CUSTOMER ANALYSIS =
                 CUSTOMER KNOWLEDGE =
                                 INCREASED CUSTOMER VALUE

At Tech4T our focus is on growing customer value. This requires reliable data and the ability to analyse both customer and transaction data. Our staff are experienced users of SPSS data analysis software and over the last 15 years have developed many powerful scripts and methodologies to analyse customer data every-which-way.

We also use FastStats Discoverer for ultra fast 'train of thought' analysis, profiling and scoring, and AnswerTree (CHAID) and 4Thought (Neural Network) for response and predictive modelling. Results can be presented in many ways including marketing and business dashboards as per the screen shot shown here. 

Our data enrichment, predictive models and scoring approach to targeting help marketers reduce non-responders and individuals likely to result in bad debt from their promotional mailing lists. By using scoring to better target promotional campaigns, marketers can improve response rates by up to 30%, improve customer value quality by circa 15%, and usually reduce mailing costs by more than 50%, all whilst increasing the customer lifetime - often by as much as 40%.

Click here for further details on customer knowledge and how this can be applied.