How to stand out in the mailbox


Email is the most used marketing channel, with 269 billion sent and received every single day. This demonstrates how competitive the channel is. But it’s still worth the effort, for every £1 you invest yields on average £28, representing a return on investment that no other channel can compete with. But to reach those lofty heights, we must ensure the content is relevant for the audience.


Subject Line

Your subject line is the proverbial first impression, are you the hot guy walking down the street with swagger or the guy eating his bogeys on the loser? This is how you set your stall out, make that first impression.


Creativity is the key to an engaging subject line, but you must keep within restrictions. For example, make sure you’re not over elaborating on what it is you’re offering, no one enjoys feeling like they’ve been tricked into opening. Here’s a short checklist to use as a guideline:

  • Short and catchy
  • Relevant to the content of the email
  • Easily understandable
  • In line with brand values


One factor that has been shown to drastically improve email open rates is personalisation within the subject line. After introducing personalisation here, marketers have seen a rise of 50% in open rates. Consumers want to feel like you’ve taken a personal interest in them, and feel valued.


Email Frequency

The frequency of the emails you send is defined by the objective of the campaign or customer journey. As long as the content remains relevant and appropriate the audience engagement will increase through each interaction. This could happen with 2 emails in a week, or conversely, 10 emails in a day.


I myself receive hundreds of emails each day and don’t have time to open them all. I tend to prioritise the ones from brands I know and respect. So for a new company entering my mailbox, a welcome email after I’ve just signed up is imperative, along with regular communication, to retain the context and keep them top of mind.


Research supports this where it has been found that consumers want companies to speak to them on a weekly frequency. Keeping that regular flow of communication maintains and fosters the relationship. Device compatibility is pivotal, if your target segment view their emails on both mobile and desktop devices, ensuring the email uses responsive design and has support for varied email clients should be top of the list.


Key Metrics

To improve the future, we must evaluate the past. Seeing what was successful and what wasn’t gives us the necessary insight to evolve our campaigns, and cherry-pick the elements we want to keep and discard the ones we don’t. This must be done both quantitatively and qualitatively.


Quantitively, open and click-through rates are our core metrics; this identifies the traffic and engagement of the messages and ultimately shows whether the campaign has achieved the desired objective. These percentages offer us a strong basis on which we can evaluate the core elements of the email but don’t give us the full picture. That is where qualitative evaluation comes into play. What thoughts and feelings an email provokes are important to understand, or whether it’s just too bland. But this isn’t as hard to conduct as you may think. A simple test of the campaign in-house, is more than adequate to find major holes or problems.



Email maintains its position as the most used marketing channel, and that’s for a good reason, it’s the most effective. But with the extremely high volumes and levels of competition comes the inherent difficulty of standing out. It always has been, and always will be, about sending the right message to the right person at the right time. But this just drives us to be better marketers, which is what we want right?

How to maximise Halloween marketing


With Halloween comes a multitude of dodgy puns, brands jumping on the holiday bandwagon and those pesky egg-throwing teenagers. Halloween provides a great marketing opportunity, but needs smart implementation to ensure you stand out from the crowd. We’ve listed the common pitfalls of Halloween marketing, and a checklist to make sure you’re optimising the holiday.


Crowded Space

So, our first concern is the biggest; crowded space. Everyone is trying to take advantage. It is a safe bet that if you’ve decided to leverage the holiday, your competitors are as well. This elevates the level of competition, not only operating within the same industry, but having concurrent marketing efforts following the same theme. Without doing something different, there’s every chance your campaigns will be too vanilla and just disappear in the noise.


The need to be innovative and unique is even greater, evaluate last years campaign, retain the elements that were effective and evolve. But most importantly, don’t be afraid to try something new! Put yourself out there, if you make enough noise, you’ll not only have successful marketing, you’ll also crush your competitors and sit top of the pile.


Consumer Spending

It’s not all doom and gloom though, holidays bring an increase in consumer spending! Now it’s just about getting them to spend with you, and how can we do this? Nurturing! Drip-feeding relevant and contextual content implants you into the consumers thought process. This is preferable to poorly targeted email blasts of promotional content and discounts that can wind people up to the point of unsubscription.


Start your campaign early and slow, start dropping yourself into the space, start creating themed content and reminding people that Halloween is just around the corner, and think about your products! It’s amazing how many companies email me on Halloween trying to get me to order a costume, on the actual day! Even if I hadn’t already sorted a costume, it wouldn’t arrive until at least the day after! Make sure you understand your product portfolio, and when customers would be looking to purchase.



  • Start early
  • Plan ahead
  • Schedule content
  • Adapt the holiday to suit your customers
  • Run a nurturing campaign
  • Innovate



Factor Halloween into your Q4 marketing activity, and plan well in advance what marketing collateral you’ll need, then load all your messaging into some good automation software and watch the results flow in!

Negative emotions produce positive outcomes


How do brands align themselves with consumers and create loyalty? And how does this affect their emotion towards brands they favour and brands they don’t think of positively, and how does that affect their perception of individuals associated with these brands? These are all issues that marketers need to understand before positioning themselves in the market.


In/Out Group Mentality

Some brands operate with a certain level of prestige associated with them, and it’s not just your elitist brands. All your high street brands will be doing the same. Take celebrities for example; they’ve developed themselves as a brand, and exhibit this better than anyone. Justin Bieber has his ‘Beliebers’, Beyonce has the BeeHive and Katy Perry has the Katy Cats. This offers the fans a distinct, recognisable tag and aligns them with their favourite celebrity, making them feel connected. This then positions them as a firm member of their in-group, making them more receptive of material and products surrounding the celebrity and less receptive of rival groups material.


Companies want this exact same thing, they want you to feel an affinity with them and connected. This is why they talk in the first person and as if they are your friend, they want a human, personal relationship with you. They’ll often say you’re part of the family or their success, attempting to build a connection. This all makes you part of the in-group, and once you’re in, you’re much more valuable to the brand.


That’s why tactics such as personalisation or enhanced targeting have become common practice within the marketing industry, they all want to make you feel a positive emotion for them, and this is how to elicit it. Knowing the complete picture and utilising features such as dynamic content allow marketers to make it seem as if they’ve handwritten each and every email, building that affinity.


To put this into perspective, in your friendship groups you’ll know a fair bit about each other, and your conversations will flow easily, you’ll ask them about their new job or the house they’re looking at buying, and they’ll like that, but if someone talks blankly at you you’ll become disengaged and perceptions of that individual might change. This then leads to that individual not being as ‘in’ as your friends, who take an interest in an open conversation. This is the holy grail for personalisation, developing an in-group, and an open conversation.



Schadenfreude relates to seeing the joy in another’s misfortune. So for companies, this relates to them directly and also for every stakeholder. This links to the in/out-group mentality, individuals will derive joy from seeing a mishap happen to someone sporting a brand they view as the out-group. A good example of this is First Direct Bank, they recently won the award for best service, and created an advert based upon this. Here they’ve seen the joy of their competitors not succeeding and looked to leverage it to improve their position in the market. I’ve added the advert below:


Schadenfreude can create brand loyalty, or alienate customers altogether. Brands can gain loyalty from their own advocates and supporters by targeting misfortunes within other brands, but while doing this it can push those advocates of the brand suffering misfortune farther away, and not gaining market share from them. But if it is exhibited effectively, the rewards can be massive, harming a competitor while improving your own position.


Also if schadenfreude is displayed too often by companies, a brand can be labelled as combative and gain a reputation, which can transfer negative implications onto the brand and make them less attractive. This affects the perception from existing and potential customers, affecting their ability to both retain and increase their customer base. Think about it, would you carry on buying your favourite chocolate bars if the brand continually attacked the quality of it’s competitors?


From the consumers perspective, when they display schadenfreude, it demonstrates a level of connection, how disconnected they are from one brand and how connected they are to another. This can provide valuable information for brands, by being able to explicitly see who supports and challenges you gives you the ability to analyse your brand advocates. Once this is has been analysed, you then have a true reflection of who your brand resonates with. From here, you can more effectively plan your marketing activities with tailored retention content and adapted acquisition messaging.



Many different factors affect the consumer mindset, and marketers must be wary of these. What we think of as erroneous information might enrage someone, or what we think is an acquisition campaign might be better suited to our existing base. Being able to understand these elements of the consumer mindset greatly increases the chance of hitting them with the right message, at the right time.


It’s not just about knowing Who to talk to, about What and When, it’s equally important to know How to talk to them.

Using RFM modelling to generate successful customer segments

RFM (Recency, Frequency, Monetary) analysis is a proven marketing model for behaviour-based customer segmentation. It groups customers based on their transaction history – how recently and how often they bought, and how much they spent.

It enables the marketer to divide customers into various categories or clusters who are more likely to respond to promotions or future personalisation services.

RFM has its roots in Direct Marketing

Bult and Wansbeek originally introduced the concept of RFM in 1995. It was used effectively by catalogue marketers to minimise their printing and shipping costs while maximising returns.

The advent of computers made it even easier to perform RFM studies because customer and purchase records were digitised, the logical progression was to take these catalogues online to become websites. An extensive study by Blattberg et al. in 2008 proved RFM’s effectiveness when applied to marketing databases. Numerous other academic studies have also validated the use of RFM in reducing marketing costs and increasing returns.

The power of three

We all know that valuing customers based on a single parameter is flawed. The biggest value customer may have only purchased once two years ago, or the most frequent purchaser may have a value so low that it is almost not profitable to service them.

One parameter will never give you an accurate view of your customer base, and you’ll ignore customer lifetime value.

Calculate the RFM score by attributing a numerical value for each of the criteria. The customer gets more points if they bought in the recent past, bought many times or if the purchase value is larger. Combine these three values to create the RFM score.

This RFM score can then be used to segment your customer data platform (CDP).

Customer Segments using RFM Modelling

Analysis of the customer RFM values will create some standard segments, a table of suggested segments is listed below.

Think about what percentage of your existing customers would be in each of these segments. And evaluate how effective the recommended marketing action can be for your business.

This RFM segmentation will readily answer key questions for your business:

·       Who are my best customers?

·       Which customers are at the verge of churning?

·       Who has the potential to be converted in more profitable customers?

·       Who can you view as lost customers?

·       Which customers must you retain?

·       Who are your loyal customers?

·       Which group of customers is most likely to respond to your current campaign?

RFM Score Calculations Simplified

RFM values – to calculate the RFM score you will first need to identify each customer’s RFM values.

Recency (R) – period since last purchase.

Frequency (F) – number of transactions.

Monetary (M) – total money spent, often called Customer Lifetime Value (CLV)

A example customer may then have a R-value of 1 week, F-value of 5 transactions and an M-value of £2,567 (CLV).

Applying RFM score formula

Once you’ve identified and assigned the RFM values from the purchase history, you can calculate a score for recency, frequency and monetary values individually for each customer.

There are two common options for ranking the RFM values on the scale of 1 to 5:


Example: If a customer purchased within last 24 hours, assign them 5. In last 3 days, score them 4. Assign 3 if they bought within the current month, 2 for the last six months and 1 for everyone else.

Therefore, the range for each score has been pre-defined. Range thresholds are based on the nature of the business. You would then define ranges for frequency and monetary values in the same way.

You should choose criteria that are relevant to the purchase cycle and product value, e.g. an M-value of £2,500 might seem high, but if you sell holidays at a minimum purchase value of £2,500 it’s not out of the ordinary.

This scoring method depends on the individual businesses – since they decide what ranges they consider relevant and appropriate.

There are limitations with this option, as the business grows score ranges may need frequent adjustments. What you thought was a high frequency or monetary value in 2017 may be quite different in 2018 once you analyse the data. This may cause problems with how you deal with your previously high-value customers if they are relatively no longer as valuable as they once were. They may now be incorrectly in the top tier of your loyalty programme.


Quintiles are like percentiles, but instead of dividing the data in 100 parts, you divide it in 5 equal parts. Quintiles work with any industry since the data itself defines the ranges; they distribute customers evenly.

Ultimately, you will want to end up with 5 bands for each of the R, F and M-values, this can be reduced to bands of 3 if the variation of your data values is narrow.

The larger the score for each value the better it is. A final RFM score is calculated simply by combining individual RFM score numbers. There are two ways to do this:

1.     Addition – this is achieved by simply adding the three scores together, e.g. Mr Jones has a Recency score of 4, a Frequency score of 2 and a Monetary score of 5. His RFM score would then be 4+2+5=11. By using this methodology, the maximum value would be 15 and the minimum being 3.

2.     Concatenation – this is achieved by linking the three scores together, e.g. Mr Jones has a Recency score of 4, a Frequency score of 2 and a Monetary score of 5. His RFM score would then be 425. By using this methodology, the maximum value would be 555 and the minimum being 111.

The Hive Marketing Cloud Customer Data Platform allows the user to choose either option to grade the RFM values using either fixed or dynamic decoding of the data.

Utilising the RFM Data

There are many different permutations of the R,F & M scores, 125 in total, which is too many to deal with on an individual basis and many will require similar marketing responses. The solution is to segment using the standard 11 personas we suggested earlier.

Each customer is placed into their corresponding segment based on their scores. Frequency and Monetary value are combined to reduce the possible options from 125 to 50. It is logical to combine these as they both relate to how much the customer is buying. Recency is more about the customer re-engagement levels.

The table below shows the destination segments along with the target ranges for Recency and combined Frequency/Monetary scores.

Applying RFM Segmentation to your business

In the brave new world of the Customer Data Platform and email marketing automation, it is possible for a business to use the above segmentation to create automated journeys that nurture customers with relevant and contextual messages that help grow their Lifetime Value and Brand Engagement.

RFM analysis helps your business optimise its marketing operations: better email marketing, higher customer lifetime value, successful new product launches, outstanding user engagement and loyalty, lower churn rate, better ROI on marketing campaigns, success in remarketing, a better understanding of your business, overall higher profits and lower costs.


RFM analysis was first created to optimise spend for direct marketing so that expensive catalogues were not sent to customers who would not convert, and this can now be leveraged in today’s omnichannel marketing.

Knowing who is most likely to respond to certain messages allows efficient assigning of budget and identification of the next best action required to optimise Customer Lifetime Value (CLV).

The Hive Marketing Cloud includes out-of-the-box RFM analysis for your business so you can hit the ground running if you want leverage your segmentation to grow customer engagement and value.