It gives marketers the ability to contextualise how consumers move from being unaware prospects to converted brand advocates. It was originally conceived by Elias St. Elmo Lewis an American ad agency owner who was operating out of Philadelphia in the early 1900s – so yes, it’s an old idea. Lewis conceived the idea that you have to take consumers on a journey to purchase, advising The Bankers magazine in 1909 to “attract attention, awaken the interest, persuade / convince”. Originally this was his formula for writing a single piece of advertising copy, but in time this evolved in to the Awareness-Interest-Desire-Action (AIDA) model which tracks a hypothetical consumer path to purchase over time.

There are two important aspects to the sales funnel model:

First, it recognises that consumers move through cognitive, emotional and behavioural stages as they move from unaware prospect to engaged buyer. This has implications for the development of creative advertising and many aspects of media planning and buying.

1. Awareness – requires cognitive change (learning)
2. Interest – is an emotional state (comfort, reassurance)
3. Desire – is a state of need recognition that is partly emotional and partly rational
4. Action – is a rational behaviour to satisfy need

In marketing terms, the messaging and media channel selections that influence awareness and interest can be significantly different to the messaging and media selection required to drive behavioural change (purchase) once interest and desire has been created.

Second, it is an hierarchical model in that it takes consumers on a linear journey from being unaware to being a customer. Because it’s an hierarchical model, a prospect has to move through each stage to get to the next, even if this happens very quickly.  The reverse logic of this hierarchy is that a consumer won’t buy unless they are interested and can’t be interested unless they are aware.

Criticisms

Critics of the sales funnel model argue that there is little empirical evidence to support the concept (Demetrios Vakratsas and Tim Ambler, “How Advertising Works: What Do We Really Know?” Journal of Marketing Vol 63 1999).  More recently the advent of digital media has caused the traditional sales funnel approach to be questioned with critics arguing that the path to purchase is no longer a simple funnel, but a much more complex set of interrelated touch points and movements.

Supporters

Whilst many critics observe that the funnel model has limitations, no better model has been proposed to date. In the absence of any other effective model, the sales funnel model has some heavyweight supporters.

Mark Ritson, a leading commentator on marketing globally and a former professor of marketing at London Business School, argues that the overall model is a strategic planning tool that should not be evaluated against tactical needs. He has said of the funnel:

“If you think the sales funnel is dead, you’ve mistaken tactics for strategy. Reports of the death of the sales funnel are greatly exaggerated. Consumers might be bombarded by media and marketing from all angles, but marketers must still understand how to influence their journeys towards a purchase.”

“The sales funnel precedes the invention of television, direct mail, telemarketing, cinema ads, the internet and smartphones. Each and every one of these technologies has changed the tactical options available to marketers, but the essential challenge of marketing strategy and the enduring value of a properly derived sales funnel remain undimmed.” (in Marketing Week 2017)

Patrick Barwise, also of LBS and Thomas Barta in their book 12 Powers of a Marketing Leader also note that:

“A marketing model that everyone understands is worth ten times more than a complex one that nobody gets. One examples of this is the marketing funnel. Using it allows you to say things like “only percent of people prefer our brand. We need to increase brand preference because 40 percent of all those who prefer us end up buying us.”

Adobe have also stated the following in their Adobe Digital Marketing Blog:

“A funnel-type breakdown is helpful because, in the most ideal use of this idea, it helps us organise our efforts into tiers—picture a series of horizontal cuts across your funnel. At the top of the funnel, we just want to be noticed. As things progress, we retain interest by satisfying the needs of the consumer (earning ourselves a relationship), before finally looking to close at the funnel’s bottom. Even after the sale is complete, the follow up and service we provide continues to serve the funnel, as repeat purchases, upgrades, etc. come into view.”

Conclusion

The sales funnel remains an important planning tool for strategic marketers.  This is mainly because no viable alternative exists. Currently, there is no other model that can offer at least the same standards of explanation, logic or utility. So, it seems that for the time being, the sales funnel model is easy to criticise but much more difficult to replace.

The post What is the sales funnel and is it alive or dead? first appeared on Marketing IQ.

Warm Direct Mail – mailings to your active customer file: In our experience, warm direct mail, i.e. DM sent to your customer file should deliver a response rate of between 1% and 5%. The average figure is around 3.5%.

Cold Direct Mail – DM send to prospects via a “cold” list: Response rates here are lower as the consumers you are mailing are less familiar with you and your brand. Typically 0.5% to 1.5%.

The DMA in the UK cites a response rate of 4% and claims that overall 7% of recipients will take some kind of action as a result of receiving direct mail.

The DMA in the US has produced a lot of information in its 2015 Response Rate Report and cites response rates of 3.7% for a house list and 1% for a cold prospect list.

The post Direct Mail Response Rates first appeared on Marketing IQ.

CRM has never been perfect. Traditionally, the term CRM has meant email, direct mail, SMS and phone. These are ‘push’ communication channels. Brands push their message out to their customer base. Push communications have always had a problem; they are by nature interruptive, as such they risk being seen as intrusive or irrelevant at time of receipt. This is just one of the reasons why many forms of DM based CRM are still referred to as ‘junk mail’ by consumers. Other reasons for ‘junk’ status are that these communications are often not requested, they’re irrelevant, they’re not green, and they leave your customer with the feeling that you are trying to persuade them to do something they may not want to do. In short, people like being in control. By pushing your message into your customers’ lives you threaten that control and risk being ‘junked’.

The advent of social media offers us the opportunity to overcome these issues and move towards a more perfect world in CRM. With its ability to aggregate, assemble and cluster groups of like minded individuals social media allows us to address and overcome the junk issues listed above. Social media gives brands an opportunity for a radical re-think of what CRM is, how it works and how we deliver it. Let’s look more closely at the sources of “junk mail” categorisation and examine how social media may make CRM a more involving experience:

1) Lack of control: Junk mail is called junk mail because it’s not requested. In the social media world consumers control the dialogue; they do the requesting and they are in control. As a brand you are not imposing yourself on the customer. You are simply there for them when they want to engage with you. This is a different dynamic to traditional CRM. It puts the customer in control of the conversation and that’s where they want to be.

2) Irrelevance: Junk mail is called junk because it risks being irrelevant at the time of receipt. Here’s where social media really scores. If you allow the consumer to control the conversation then they are likely to contact you only when they have something important to say. Consumers will either like product, dislike a product or need more help with it. If you are dealing with these issues for customers at a time of their choosing then you are more likely to maximise the relevance of your communication.

3) Environmental issues: Junk mail is called junk because prospects and customers think it’s not green. The statistics around DM paper wastage are staggering and the DM industry should move forward from denial to recognition. It has been estimated that the UK is subject to more than 500,000 tonnes of waste paper through DM every year. Even if it’s recycled we should be thinking about the energy costs of this mammoth recycling task. Whilst all social media has some costs, they are minuscule compared to the environmental costs of paper manufacture, printing and recycling of millions of tonnes of DM. In 2011 brands must be seen to be environmentally aware and social media allows this to happen by reducing your dependence on less environmentally friendly paper-based forms of communication.

Social media gives us the opportunity to reverse the drive train in CRM. It’s time we used the internet to move from putting things into peoples’ homes to inviting people into our brands. It’s time we stopped trying to control the customer. It’s time we put the customer in control of us. It’s time we moved from push to pull. There nothing new here, marketing theory dictates that companies should be responsive to customer and consumer needs. The problem has been that until the advent of easy to use social media networks being open and responsive was easier to say than do.

By moving into social media CRM we open up our relationship with consumers. This sends positive signs. Companies that are prepared to openly discuss issues between themselves and their customer base will be perceived as accessible, caring and confident in the way they provide products and services. These are all valuable brand attributes.

Of course running CRM in social media where all comment can be seen by others requires marketers to have a high level of confidence in the brands and services they are delivering. But rather than being seen as a hurdle to be overcome, this should be seen as a useful litmus test of a company’s relationship with its markets. If as a brand you don’t feel confident enough to open up your CRM in the social media environment then that tells you something about the prevailing relationship you have with your customers. If thinking about social media raises negative issues then you should use this as an opportunity to clarify and address those issues.

And if you are confident that you can press the social media button now, then your openness can only serve to increase the confidence customers and consumers place in your brand.

The post Is Social Media CRM’s new platform? first appeared on Marketing IQ.

Here’s an example: Let say you sell 10 products. It may be the case that all purchasers of product 8 are: 1) in a certain geodemographic group, 2) married with more than one child and 3) own more than one car. All these factors can be analysed and combined to predict the likelihood of any consumer in your database buying product 8. Usually this combined measure is referred to as a ’score’ i.e. a figure which represents the presence or combination of certain variables in the consumer record. Once you have developed your scoring model you can rank all customers by their score. When you’ve stripped out those who have already bought product 8, you are left with a set of high potential prospects.

Predictive modelling can also be undertaken based on transactional information about past purchases. Going back to the 10 products, it may be the case that 80% of people who buy product 7 have previously bought products 2, 5 and 6 and in that order. So we can say that people who have bought products 2, 5 and 6 (in that order) but who have not yet purchased product 7, are much more likely to buy product 7 than everyone in your database. Again a score is attached to these behaviours and that score can be used to rank your prospects in terms of untapped sales potential.

Of course as well as predicting purchase behaviour, these techniques can be used to predict risk. In credit assessment for example, it may be the case that those customers who have certain demographic characteristics combined with a certain type of past purchase behaviour are highly likely to default on a credit agreement. This is sometimes referred to as credit scoring. If you are rejected for credit at a bank or in a shop it will be because your data has been analysed and your credit risk score is deemed too high or low to meet the criteria of the lender.

These predictions can help you target your communications very efficiently and also help you control commercial risk in customer behaviour. What’s interesting about these techniques is that they help both the marketing department and the finance department. Marketing delivers customers who are both highly likely to convert to sales or high lifetime value whilst at the same time, producing customers who are less likely to cause problems for the finance department. Overall, this means that the resources of the business are being better utilised.

The post What is predictive modelling in marketing? first appeared on Marketing IQ.

At the most basic level your database should contain a name and address for each record. The name and address can give you valuable information. The postcode in the address opens up the potential for geodemographic analysis using tools like ACORN or MOSAIC. These tools work by grouping consumers into clusters of similar people based on the types of neighbourhoods they live in. The principle behind these systems is simple; birds of a feather flock together. The owners of these segmentation systems undertake research into the clusters they have developed. For example, Cluster 1 may contain people who are known to be affluent pre-retirement couples with children who have left home. Research may show that these people are three times more likely to drive a certain car, purchase certain electrical products or take holidays to certain destinations. So from just the address record you can build a much wider picture of the record in question.

But the full name and address have even more potential. They can be used to match your customer file with an external data file containing more information about the same person. This data can come from many sources, but more often it comes from lifestyle surveys. If a customer in your database has completed a lifestyle survey then you can buy supplementary information to significantly expand what you know about that person.Here’s an example. You may only know the name, address and age of a customer. But if that record can be matched with a respondent to a lifestyle survey then you can see the answers to tens or even hundreds of other purchase preference questions that person has shared. For example, you may be able to see what type of car they own, when it was bought, when they intend to replace it. They may even tell you what type of car they are considering next.

If you have transactional data then you are able to undertake an analysis of the types of products and services bought by the customer. From this data you would be able to say that a customer owns products X, Y and Z and you will probably know when they bought those products. You will be able to see how the often products are purchased and the preferred means of payment. If there is cyclical behaviour in the purchase pattern you may be able to predict when this customer is likely to purchase those products again.

With these high levels of customer understanding you are able to take a lot of the guesswork out of marketing. You can be much more focussed in terms of selling specific products to specific individuals. As a result you response, conversion and customer value rates are likely to improve significantly.

The post What can a database record tell us about customers? first appeared on Marketing IQ.

• Exactly who buys a given product or service
• Detailed information about the characteristics of those buyers
• Which other products and services they buy
• Which product and service offers they find most attractive
• Which buyers buy more of certain types of products
• How you can find more buyers with the same characteristics

These data analysis techniques can be applied to all types of customer data – whether it’s for a retail business, an online business or a call centre based business. Insight from data analysis can be applied across a wide spectrum; from adding inspiration to a creative brief through to changing a company’s entire business strategy.

You may think the claim that data analysis can change the destiny of a business is rather grandiose. But I can can think of two examples of breakthrough data insight from the same category that ended up contributing millions in additional brand revenues.

Sainsbury’s  – Sainsbury’s agency AMV were tasked with increasing the then ailing retailer’s sales by £2.5bn over a three year period. A seemingly impossible challenge until viewed as a data question. The AMV team calculated that £2.5bn equated to £833m per year which in turn equated to £16m per week.  It still looked like a big number until the AMV team considered that Sainsbury’s handled 14m customer transactions per week.  Then the target equated to just £1.14 per transaction. The brief to increase sales by £833m per week could be redefined as increasing each existing transaction by just £1.14. Now the target not only looked attainable, but this data insight led to the idea that lots of small changes could make a big difference.  From this insight came the campaign idea that consumers should “Try something new today”. By asking customers to ‘try something new’ they were able to persuade customers to spend at extra £1.14 every time they shopped.

Tesco – The Tesco Clubcard is now legendary as both a customer loyalty card and a source of information about customers.  Up until the introduction of the loyalty card, many retailers didn’t know who their customers were. And if they didn’t know who they were it was difficult for them to gather the data that allowed them to understand individual customers better. With the Club Card this all changed. Tesco were able to develop individual data driven relationships with their customers.  They were able to understand customer needs better and in doing so they gained competitive advantage over their rivals.

The post Marketing data analysis gets you closer to customers first appeared on Marketing IQ.