The grey area between fundraising and marketing is grey no longer!

As a marketer specialising in data-driven techniques I spend a lot of my time helping charities understand the relationships they have with their constituents through analysis of their data so that relationships can be developed in a way that will be most productive for the charity and most acceptable to the constituent. The management of the relationship is a marketing function.

It is evident that not everyone that a charity benefits from is a donor; some constituents need to remain at arm’s length and are happy to buy merchandise, attend events or even organise appeals but will not ever be or want to be seen as donors. However their activities still raise funds for the charity. Any attempt to convert them – even from ad hoc donor to committed giver – can put them off altogether. This is what was meant by delivering the right message at the right time to the right person.

We don’t have to go back  too far in history to find the definition of Marketing, only about 50 years: “the identification of a need and the addressing of that need through efficient and effective use of an organisation’s resources, to make a profit”. For nfp’s read profit=funds. I don’t necessarily agree that fundraising should necessarily be a part of a marketing department, but marketing techniques certainly support fundraising ; however in a smaller charity fundraising  will sit most comfortably within a marketing environment rather than finance, admin or general management.

Scoring your customers

Companies must continue communicating with their customers through a consistent strategy that is driven by customer insight. Rating current customers is not solely based on how much they spend but has as its basis the classic RFM (or RFV in the UK) model that creates a score based on recency, frequency and monetary value. My recommenation is not to stop there but to add more elements such as Returns, Complaints, number of enquiries, length of time they have been a customer and create a contact plan that reacts to the dynamics of these scores.

Often we will identify cohorts of customers that represent bad business. The solution can either be to review the business process for how you do business with them, e.g. relegating them to an ‘exclusive’ on-line relationship where the cost of managing them is reduced rather than taking up the time of a salesman or telephone agent; alternatively the bullet might have to be bitten and you resign the account.

However, building segmentations or communities of valuable, profitable customers by profile and comparing their behaviour will also drive the communication; but don’t just use it to determine when to make contact. Customer insight should also drive the ‘next best proposition’ for each customer so that the sales person can be proactive in establishing opportunity. What you know about your customers can also be used to drive new customer acquisition by comparing prospects’ profiles with your customers and determining the best proposition.

Customers rate companies with whom they deal by the quality of the communications and this means relevance, personalisation and timeliness.

CRM training is more than just knowing what key to press!

I am finding more and more that companies go ahead with the introduction of Customer Relationship Management (CRM) technology without considering all aspects of the training requirement. As part of the universal application of CRM across an organisation, it is important to understand where there is a need for new skills and perspective. Sure, the software provider will provide training on what buttons to press to access a customer or to send an email but consideration is rarely given to the use of the data now at the salesman’s or marketer’s fingertips. When introducing CRM to an organisation it is essential that effort and budget is put into bespoke training in the use of data so that the greatest benefit is realised out of the investment. Usually skills transfer for users will cover:

­      – An understanding of the CRM culture and the company data strategy

­      – Understanding data (data quality, the need for accuracy, etc)

­      – Skills in data usage

­      – Skills in direct marketing and relationship management

­      – Reporting concepts

Without this the users will become frustrated because they will not achieve the expectations of the management and will either leave (often taking a valuable resource with them) or just not use the technology which means a wasted investment.

Where does the provision of marketing information belong?

There has been much debate about whether the business or IT should lead information provision. IT is unlikely to be in a position to fully appreciate how the business could take advantage of the data because they are not involved in the daily process of sales and marketing of their company’s products and services. But equally, the business not really wanting IT to be involved in analysis and reporting, do not fully comprehend the nature and nuances of the data that is available to them, after all it was IT that designed the systems in the first place!

Without a thorough understanding of the data it is highly likely that irrespective of who performs the analyses the wrong conclusions will be reached.  Despite some product vendors exploiting this divide of opinion to their own advantage, it has been proven beyond doubt that the greatest successes come from those organisations that have created a culture where business and IT truly work together with complementary objectives and common business goals.

This is by no means an easy recipe for success with possibly years of divided working practices and politics to overcome but with strong leadership and active project sponsorship at the highest-level of an organisation success will be inevitable.

Can you risk leaving travel customers to make up their own minds?

A recent survey by Directline Holidays concludes that  Word of Mouth is most trusted recommendation when it comes to booking the right trip.

Travel companies have the ability to build and nurture such tactics from within their own customer data. Considering the customer’s overall relationship with the company will assist in creating a customer journey that delivers advocates who will either perform actively or passively for the brand.

Active advocacy is where the satisfied customer will recommend the firm to their relations, friends and wider acquaintances; sometimes a reward sweetens the process. Passive advocacy is where using what you know about your best customers enables you to ‘clone’ new customers who are likely to appreciate similar destinations and levels of service and so behave in a similar manner.

All of this can achieved by collecting and maintaining the right data about customers, engaging them in a relationship and progressing them up the “loyalty staircase” to advocacy.

The survey also stated that “almost a quarter of those surveyed said they were not influenced by anything” (source: e-tid 20/8/12). Can you risk your customers being left to their own devices? Make sure they are influenced by their peers, by relevant propositions and a customer relationship that delivers real benefits.

Travel companies are lucky….

Travel businesses are luckier than many other sectors. They have data on their customers and their customers’ enquiries and purchases and so can derive tremendous benefits from analysing these vast amounts of data, uncovering hidden nuggets of opportunity among their data, once they know how to go through it systematically and leverage the effect on profitability. Analytics software is useful, but some concept of what should be analysed is also of value.

We will often create a RFV model for tour operators or travel agents, combining Recency (of last booking), Frequency (regularity of bookings) and Value (either total spend or average booking value, for example) to create a score for each customer. We have found that adding additional elements expands the score from the 3-letter acronym to a multi-letter acronym such as RFVCIA where you add on the instances for example of Complaints, Introductions to friends or relations and Abandoned on-line baskets committed by the customer.

This score then becomes a comparator between customers, a selection criterion for campaign or proposition and changes in the individual’s score over time become a valid measure of success of the relationship.

Applying demographic, lifestyle and psychographic profiling provides an even more granular segmentation and the ability to apply the concept to prospects, with the benefit of making relevant offers to convert them to customers.

This leads us no to the second most frequent model we create: the market basket model. Knowing what destinations or types of travel different customers prefer is fundamental in programme planning, product development and in driving cross-selling or up-selling opportunities. Being able to compose and analyse the combination of travel products that customers buy will enable the travel marketer not only to determine how best to develop the business with those customers, but, by extrapolating this information, estimate the buying potential amongst the remainder of the customer base.

The often-cited (and some say apocryphal) “beer and nappies” story is an illustration of what can be achieved. Those that don’t know the story can read it at www.dmcounsel.co.uk.

This type of analysis is certainly not the exclusive domain of supermarkets or Amazon.com (we’ve all encountered their ‘people who have read this book have also bought this other book’).

If you can identify a customer as having purchased a product then market basket analysis such as was applied here can deliver cross-sale opportunities by making the right proposition in communications, positioning complementary products together on the shop floor or on the website or catalogue page or driving the pitch made by a telephone sales agent.

Such models can be created without investment in analytical software and can be applied in rules-based workflow and business process, with the dynamics regularly reviewed and the model(s) enhanced.

The extended 3-letter acronym to drive retail direct sales

Analytics software is useful, but some concept of what should be analysed is also of value. Retailers will often create a RFV model, combining Recency (of last purchase), Frequency (regularity of purchase) and Value (either total spend or average order value, for example) to create a score for each customer.

We have found that adding additional elements expands the score from the 3-letter acronym to a multi-letter acronym such as RFVRCA where you add on the instances of Returns, Complaints and Abandoned on-line baskets committed by the customer.

This score then becomes a comparitor between customers, a selection criterion for campaign or proposition and changes in the individual’s score over time become a valid measure of success of the relationship.

Applying demographic, lifestyle and psychographic profiling provides an even more granular segmentation and the ability to apply the concept to prospects, with the benefit of making relevant offers to convert them to customers.

Such models can be created without investment in analytical software and can be applied in rules-based workflow and business process, with the dynamics regularly reviewed and the model(s) enhanced.

Is your marketing communication model still valid?

How long have you been using the same communication model? You need to challenge its validity. Models will outlive their validity within 12-18 months.

Ask yourself:

  • Can you improve the return on your campaigns?
  • Do you need to increase protection against churn?
  • Is the profile of your customer base changing?
  • Do you think you can increase your marketing efficiency?
  • Does your current model encompass all your marketing channels?
  • Do you need to identify new opportunities for cross sell and up sell

Marketing analytics enables rapid discovery of valuable insights into how and why a business performs in the way it does so that you can apply this knowledge to shape future success. You need to define your customers not simply in terms of revenue, but:

  • Behaviour
  • Duration of custom
  • Number of enquiries, returns, support requests or complaints
  • Frequency of business
  • Propensity to refer or recommend
  • Types of product or services purchased
  • Returns
  • Complaints
  • Preferred channels of communication
  • Response to marketing propositions

From this newfound understanding, you are able to tune services to meet customer needs and develop propositions, with the result being customers that feel valued and who are likely to spend more and be increasingly loyal.

Your business will be provided with specific details of opportunities e.g. who to contact and what proposition to present, so you can act upon the results and benefit immediately from ensuring you are employing the right strategy.

These techniques can address some of the key business imperatives uppermost in the minds of marketers:

  • The need to know more about their customers
  • How to identify and protect against churn
  • Direction for growth
  • Areas where service needs improvement
  • Pinpointing the opportunities for cross sell and up sell
  • How to get more out of the marketing budget (or the same for less)

and ensure more of the right people get the right message at the right time.

E-communication underlines the need for greater control of the Campaign Management cycle

The growth of the internet has implications on both sides of the data-driven communications equation. On the one hand, it provides an exciting and convenient medium for delivering a message to customers and prospective customers. On the other, it presents a channel for data collection that makes possible concepts that were only hypothetical in the past.

The beginning of the 1990s saw the introduction of data to drive variations in customer magazines and newsletters across a variety of media channels, bringing lifestyle “versionalisation” and reader personalization.

However, in all of these cases the systems that drove them relied upon pre-selection and qualification of the data. The influence of the internet imposes new complexities to the concept of the strategic cycle.

In a traditional, tactical direct marketing scenario, you can start with planning a campaign, which will generate a response, which, in turn can then be analysed (even a zero response can be analysed!). This analysis of the performance of the communication can then be used to fine-tune the communication strategy for the future, and so the process continues. One needs to imagine this in 3-D, more of a spiral than a circle, because, if all turns out well, the initiative will be moving the enterprise forward while the strategic cycle turns.

The key element here is control. The introduction of the campaign to the marketplace is controlled: The marketer knows when this has been done; and the expectation of response is controlled, because the execution of a campaign will generate response over which the marketer has control in terms of channel and timing.

The internet has imposed new, reduced timescales between those points in time when the relationship is measured and tested or where opportunities for collecting, verifying or qualifying information are encountered. Previously, the direct marketer could establish when a mailing or phone call was executed and within some degree of control anticipate when a response would be generated. Access to the web has reduced this element of control. A marketer can no longer engineer when a contact may encounter his message, proposition or brand. One now has to consider the implications of both broader data source opportunities and communication media. With the web and the attendant swing toward a demand-led marketing environment, with its greater customer expectation of availability, the response is no longer controlled, and your strategy must account for that factor.

For years marketers strove for one-to-one relationships relying on the traditional tactical spiral model discussed above, and its success has been commendable within the context of the available techniques. New concepts, tools and expertise now help deliver an outcome that is closer to the vision. The development of the web has coincided with an increased awareness of the availability of data within organizations and the appearance of new, intuitive data analysis tools, employing techniques that provide for the derivation of information and the definition and interpretation of patterns within timeframes conducive to achieving the required dynamics.

As companies seek to integrate their suppliers, their customers and their marketing partners in complex relationship structures, new quantities of data are becoming accessible for exchange and sharing, and the value of the data as a corporate asset is increasing.

The income of inquiries, web site hits, new data, business intelligence and market data can have a real-time effect on the way the strategy proceeds, and so the strategic cycle becomes more complex. The marketer must now be prepared for uncontrolled response arriving from customers and prospective customers drawn to or discovering the company’s web site. Similarly, as new information is acquired internally into the data warehouse from, say, the accounts system or externally from suppliers of market information and competitive intelligence, the data has to be analysed and its value to the strategy interpreted and used to automate variations in the strategy. This ensures relevance of message, continuity of relationship and maximal effectiveness of any marketing communication, getting ever closer to the “holy grail” of real one-to-one marketing.

The strategic cycle, therefore, takes on new elements, to account for the uncontrolled data entering the process and the need for aligning its value to the strategy and translating it into rapid response in terms of proposition and delivery of a communication.

The sheer wealth of information available now flowing from the web, the ability to identify and acquire it and the tools now available to manage it in all its varying formats and structures all mean that disparate data, wherever it may reside, can be made available to add qualification, enhancement or verification to a marketer’s database. The natural corollary to that is a keener degree of customer profiling and targeting, a greater level of personalisation of message, proposition and presentation, resulting in improved marketing effectiveness and efficiency.

The Power Of an MBA (Market Basket Analysis)

Businesses can find tremendous benefits from analysing the vast amounts of data they collect finding hidden nuggets of information among their data, once they know how to go through it systematically and leverage the effect on profitability.

In practice, all too often marketers are concerned with using data to drive promotion, but true insight into customers has impact on all the elements of the marketing mix.

The knowledge to be derived out of customer data can be used outside the selling or marketing communications environment. Knowing what products different types of customers prefer is fundamental in planning range, in stock control and in driving cross-selling or up-selling opportunities. Being able to compose and analyse the combination of products that customers buy, either at one visit or over time, will enable the marketer not only to determine how best to develop the business with those customers, but, by extrapolating this information, estimate the buying potential amongst the remainder of the customer base.

The often-cited (and some say apocryphal) “beer and nappies” story is an illustration of what can be achieved. Those that don’t know the story can read it at www.dmcounsel.co.uk. A notable example of this concept took place in a Spanish airport duty free shop. Analysis of the EPOS data showed a significant trend of purchases that comprised solely either brandy and cigars or whisky and cigarettes. When the airport data was matched by flight number (remember, each duty free sale has the passenger’s flight number on the transaction record) it became apparent that the first transaction type related to passengers en route to Germany and the second type related to passengers with the UK as their destination. What was also noted was that these purchases were all made within 10-15 minutes of the scheduled departure time for the respective flights. This meant that people were passing through the shop quickly at the last moment, just picking up the two most important items on their shopping list.

The management therefore put sales points for the respective combinations of products actually in the gate area for the German and UK flights, thus generating incremental sales amongst the passengers who really felt they had no time to make a purchase at the shop.

This type of analysis is certainly not the exclusive domain of duty-free shops, supermarkets or Amazon.com (we’ve all encountered their ‘people who have read this book have also bought this other book’).

If a company can identify a customer as having purchased a product then market basket analysis such as was applied here can deliver cross-sale opportunities by making the right proposition in communications, positioning complementary products together on the shop floor or on the website or catalogue page or driving the pitch made by a telephone sales agent.

You can use such techniques to determine the real cost of being out of stock of key items and the implications on supply chain. But, by combining market basket analysis with customer profiling, you unleash powerful techniques that can generate significant increases in sales.