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SPAM! Oh yes, that tender pork shoulder meat, mixed with ham and a dash of modified potato starch, packaged in a square tin housing (are you salivating at the thought?). Alternatively, and maybe more appropriately it can be described as receiving unwanted emails from unknown individuals (Janssens, Nijsten & Van Goolen 2014). According to Statista (2017) 61% of all global email traffic is labelled as SPAM. Now, I’m sure your email provider has effective spam filters in place, but if you are an email marketer it’s best to cover the basics of what not to include in your email campaign so you can maximise delivery rates, helped by the good folks at icontact. With so much deception out there, it’s easy to understand that users aren’t very trusting, making it harder to encourage them to open your email at all. This blog will help you change that through utilising a wealth of tools so you can master the art of email campaigns; less canned meat, more Michelin star melt in the mouth. Let’s get started!

Top Tip #1: Permission Email Marketing (PEM)

PEM in a nut shell is when users provide consent for companies to contact them (tick this box to receive our latest and greatest deals sort of thing). I don’t mean to get technical but it’s related to the Technology Acceptance Model put forward by Davis et al., (1989) which is used to assess how we come to accept technology (a model that does exactly what it says on the tin – Ronseal eat your heart out). The model has since been extended to adapt to the complexity of the digital environment, introducing new elements such as trust, enjoyment, usefulness, as well as attitude. These elements accompany usefulness, and ease of use, which were the two original elements (Ha & Stoel, 2009). You should consider satisfying all these factors when forming a campaign to ensure you fully satisfy the user who has so kindly given you permission. Now the reason why a user has provided consent could be endless, they might want to keep up with fashion trends so opt-in for ASOS, or have been told by a friend that they’ll receive a free cookie if they opt-in to Millie’s. Bluehornet (2013) researched further and found that 83% of recipients consent to PEM to access discounted products and services; this might be a good place for you to start. If you want to take your reading further I’d recommend reading permission marketing by Seth Godin who arguably coined the term.

Top Tip #2: Subject Line

We’ve all received an email and deleted it once we’ve read the subject line. I like to think of the users’ role as a talent judge, reviewing the company’s audition (subject line) to see if they’ve got what it takes to impress them and get through to a second round (opening the email). Wylie (2014) suggests a subject line should encapsulate curiosity and be relevant to the individual. Now if you’ve got your permission marketing all set up as suggested in top tip #1, you can maximise relevance. In regard to curiosity, this is a difficult one, you could go for the “Don’t open this email” subject line, which can be linked to the study of psychology and how thought suppression can’t be sustained very well; it can actually lead to obsession (Wegner et al., 1987); when I ask you not to think of a white polar bear, what do you think of? Point made! Although it would be nice for users to be obsessed with your emails you could alternatively go for “Understand this topic (perhaps Brexit) in 5 minutes” pulling on the heart strings of our intrinsic or extrinsic motivation to better ourselves. Ryan & Deci (2000) describes Intrinsic motivation as carrying out an act for your personal value and not for external rewards (understanding Brexit so you are aware of current affairs). Extrinsic motivated individuals seek external gratification (understanding Brexit so you can gloat to your uninformed friends); either way you might get a click. There is no hidden formula but I would recommend reading HubSpots’ 17 top tips for catchy email subject lines, and their subject line examples for inspiration.

Top Tip #3: Measurement

“One accurate measurement is worth more than a thousand expert opinions” – Admiral Grace Hopper

You’ve probably heard a wealth of  open rate, click-through rate, and call-to-action targets you should be aiming to hit. Amongst the crowd, it’s important to benchmark against the industry you are in, so you’re not comparing apples with oranges. Chaffey leads the team at Smart Insights who have collated the statistics in various industries allowing you to understand the metrics in your market in more detail.

Key metrics you should be monitoring are the following:

• Click-through rate
• Conversion rate
• Bounce rate
• List growth rate
• Overall ROI

Google Analytics is a great free tool to analyse your campaign, aided by a visual dashboard that displays large amounts of data in a friendly form factor. You can utilise this tool to its full potential by undertaking a Lynda course which will help you understand the essentials.

 

References

Bluehornet, (2013). 2013 CONSUMER VIEWS OF EMAIL MARKETING. 2013 Consumer Views of Email Marketing. [online] Bluehornet. Available at: http://info.digitalriver.com/rs/digitalriver/images/Report_Consumer-Views-of-Email-Marketing_2013_web_(2).pdf [Accessed 10 Apr. 2017].

Chaffey, D. (2016). Email marketing statistics 2017 compilation. [online] Smart Insights. Available at: http://www.smartinsights.com/email-marketing/email-communications-strategy/statistics-sources-for-email-marketing/ [Accessed 11 Apr. 2017].

Davis, F.D., Bagozzi, R.P. and Warshaw, P.R., 1989. User acceptance of computer technology: a comparison of two theoretical models. Management science, 35(8), pp.982-1003.

Ha, S. and Stoel, L., 2009. Consumer e-shopping acceptance: Antecedents in a technology acceptance model. Journal of Business Research, 62(5), pp.565-571.

Janssens, K., Nijsten, N. and Van Goolen, R., 2014. Spam and Marketing Communications. Procedia Economics and Finance, 12, pp.265-272.

Ryan, R.M. and Deci, E.L., 2000. Intrinsic and extrinsic motivations: Classic definitions and new directions. Contemporary educational psychology, 25(1), pp.54-67.

Statista, (2017). Spam statistics: spam e-mail traffic share 2016 | Statista. [online] Statista. Available at: https://www.statista.com/statistics/420391/spam-email-traffic-share/ [Accessed 10 Apr. 2017].

Wegner, D.M., Schneider, D.J., Carter, S.R. and White, T.L., 1987. Paradoxical effects of thought suppression. Journal of personality and social psychology, 53(1), p.5.

 

“Social media is the ultimate equalizer. It gives a voice and a platform to anyone willing to engage” – Amy Jo Martin

Providing Context

We all use it; some of us abuse it; some of us do it when we are bored; some of us do it when no one is looking; others do it at the dinner table; heck, I’ve seen couples do it at the dinner table together! Before your imagination runs wild I’m talking about creating and absorbing social media content. Chaffey (2017) details that there were over 2.7 billion active users on social media in January 2017, which is an increase of +21% YoY; businesses naturally want to exploit this audience and reap the benefits; this blog will help you do that with 3 top tips for success, and at the very minimum, will expand your knowledge on social media marketing.

Top Tip #1: Humanisation

When you think of social media you probably think about connecting with loved ones, friends, and friends of friends (don’t act like you haven’t stalked before). You don’t think about businesses connecting with you, aiming to be your friend, posting on your feed with language you similarly would use; humanising their campaigns to emphasise they are your friend, and that you should trust them, and should trust their product; Nielsen (2015) supports this by documenting that the most credible form of advertising is from people we know and trust. Park et al., (2015) goes a step further by conducting a study analysing language used by over 60,000 Facebook users where word clouds were created to show popular words/phrases posted by users with differing personalities (see figure 1).

This should remind you that no one size fits all; write posts in your social media campaign that address as many demographics as possible; from the party goers to the stay at home with pizza types. You can find 9 ways to humanise your brand here. Great examples of social media posts I’ve discovered can be found below.

 

 

Top Tip #2: Involvement & Co-creation

We are social animals who thrive off interaction with others. We all have an opinion on something, and enjoy hearing the words “what’s your opinion?”, whether it’s a friend or a stranger, it makes you feel like you are being valued and that your input is respected. Your campaign must engage users and stimulate customers to get involved. This is all too often forgotten as Merlo et al., (2014) suggests that businesses consider customer acquisition to be more critical than customer retention, which is a worry as acquiring a new customer is “25 times more expensive than retaining an existing one” (Gallo, 2014, p29) (think phone providers and how they try to keep your business when your contract is up for renewal, allowing you to barter the price– they know you’ll go to a competitor otherwise). Having said this, some companies are creating a bond with their customers, such as Burberry who permit customers to make design suggestions on their trench coat designs using a customer portal (Gouillart, 2012). Here are other brands who strive to involve and co-create. Remember to involve your customer and actively ask for their feedback in your social media campaigns – your engagement will blossom by doing this.

Top Tip #3: Measurement

With so much content being produced in a single minute, you can understand the perceived difficulty in cutting through the noise on social media and trying to discover relevant conversations that really matter; I present the solution of social media listening to you my friends. Zhang & Vos (2014) defines social media listening as interpreting data submitted by users on social media channels. So the question on your mind is, so what? What does this mean for me and my campaign? Using a tool like Brandwatch Analytics helps you create a granular approach where you can identify conversations globally, nationally, and by town, there is even a sentiment tool which analyses whether a post is positive, neutral or negative towards your firm. This can be hugely beneficial as Kim (2016) details that campaigns can fall into a crisis where a campaign is interpreted negatively by users. In this situation, being aware of the negative conversations allows for damage limitation. A great recent example is the latest Pepsi commercial that encountered intense criticism for trivialising the Black Lives Matter movement, resulting in the advert being pulled within 24 hours of airing.

Remember to listen and react to the conversation; if there are rave reviews on your product – flaunt it; if there are questions regarding quality – react to it. It’s best to deal with issues in the incubation stage like Pepsi did. You can also turn a crisis into a business opportunity like Bimbo did so well; customers in Mexico were complaining that one of their cake products had a flavour in the U.S which was absent in their home nation. As the conversation grew, so did the frustration, leading to the flavour being introduced in Mexico, and so with it came a $580,000 revenue contribution.

There’s One More Thing

Social media listening tools can be multiplied tenfold by employing predictive analytics that computes a vast amount of data, which is then filtered, and then induced into a predictive framework (Kalampokis, Tambouris & Tarabanis, 2013). Now this can get quite technical so I’ll conclude this blog post with a fascinating video from Golbeck (2014), informing you a little more on the power of prediction. I hope these set of ingredients in the form of top tips will have you altering your social media formula (or meth formula – oh come on, I needed to mention the TV show at least once!)

I’ll see you on the social media battlefield.

See you next week.

 

References

Chaffey, D. (2017). Global Social Media Statistics Summary 2017. [online] Smart Insights. Available at: http://www.smartinsights.com/social-media-marketing/social-media-strategy/new-global-social-media-research/ [Accessed 6 Apr. 2017].

Golbeck, J. (2014). Jennifer Golbeck: The curly fry conundrum: Why social media “likes” say more than you might think.Available at: https://www.youtube.com/watch?v=hgWie9dnssU [Accessed 8 Apr. 2017].

Gouillart, F., 2012. Co-Creation: The Real Social-Media Revolution. Harvard Business Review.

Kalampokis, E., Tambouris, E. and Tarabanis, K., 2013. Understanding the predictive power of social media. Internet Research, 23(5), pp.544-559.

Kim, C.M., 2016. Social Media Campaigns: Strategies for Public Relations and Marketing. Routledge.

Merlo, O., Eisingerich, A.B. and Auh, S., 2014. Why customer participation matters. MIT Sloan Management Review, 55(2), p.81.

Nielsen, (2015). GLOBAL TRUST IN ADVERTISING. [online] Nielsen. Available at: https://www.nielsen.com/content/dam/nielsenglobal/apac/docs/reports/2015/nielsen-global-trust-in-advertising-report-september-2015.pdf [Accessed 6 Apr. 2017].

Park, G., Schwartz, H.A., Eichstaedt, J.C., Kern, M.L., Kosinski, M., Stillwell, D.J., Ungar, L.H. and Seligman, M.E., 2015. Automatic personality assessment through social media language. Journal of personality and social psychology, 108(6), p.934.

Schweidel, D.A. and Moe, W.W., 2014. Listening in on social media: a joint model of sentiment and venue format choice. Journal of Marketing Research, 51(4), pp.387-402.

Zhang, B. and Vos, M., 2014. Social media monitoring: aims, methods, and challenges for international companies. Corporate Communications: An International Journal, 19(4), pp.371-383.

Why do you keep reciting the first 2 letters of the alphabet?

A/B testing is the process of comparing two different iterations of a webpage or application so a company can discover which variation performs better (Martin, 2015). I like to explain this using a food analogy. Think about when you purchase your favourite burger from your favourite fast food chain, and you would never purchase anything else. They suddenly remove your beloved burger and replace it with a 1 week trial of a new burger, but only in your local branch; perhaps they swap mayonnaise with a chutney. You try it and my gosh…you love it! even more so than your previous go to choice. What’s even better is that it turns out there is an increase in 30% of sales as others love the burger too. The company then decides to roll out the new iteration nationwide. That’s a successful A/B test in the physical world, but now imagine that online. Figure 1 shows 50% of visitors to a site being shown variation A, and 50% being shown variation B; we then look to analyse the % of conversions from each variation with the higher figure being the winner. Companies can then choose to conduct another A/B test (why stop when you’re onto a good thing), or go live with the winning variation so all visitors can cast their eyes on the update.

Surprising results

Hubspot details fantastic examples of A/B tests that provide unexpected results. Figure 2 shows a variation that incentivises users to pre-order a new Sims game with a discount voucher; figure 3 displays a variation which removed the code entirely. The test results revealed the variation with no promotional code increased purchase rates by 43% compared to the control group. Think about how crazy that sounds? – people just wanted to purchase the game; no incentive required. This is a great example of how conventional human opinion fails to optimise your website, and exposes that letting data decide ensures an unbiased result. You can see how companies are making this a point of parity (a minimum standard) with an intriguing Netflix presentation on how the media powerhouse uses A/B testing, found here.

So is this the God particle or is there a catch?

Roy (2001) detailed the idea of having an Overall Evaluation Criterion (OEC) which can be applied to analyse the significance of an A/B test. This doesn’t have to be limited to sales conversions (as with the burger analogy earlier) but could be to increase subscriber count, or encourage users to leave a product review. Now of course there are infinite reasons why our audience behave differently with variation A compared to variation B; we’ve got to remember that correlation doesn’t necessarily mean causation (Levitin, 2016). A user might be having a good day and naturally want to leave a positive review of a product, or they might have heard through word of mouth how brilliant an Instagram account is, so subscribed purely on a recommendation from a friend; it just so happens they are helplessly caught in an A/B test. I won’t bore you by recommending statistical text books on how you can gain accuracy in your testing but Kohavi., et al (2009) summarises that a confidence level is found at 95%, implying that the final 5% “will incorrectly conclude that there is a difference when there is none”. The study also explains the limitation of A/B testing through “primacy and newness effects” which argues that experienced users may be less efficient at navigating a website due to being shown an unfamiliar webpage (primacy effect), as well as clicking on links or calls to action purely because they want to investigate the new feature (newness effect). The study suggests running a test for a few weeks rather than just a few days in order to counteract this bias.

I can work Microsoft Word, but I wouldn’t have a clue about these science experiments?

Ok, I admit, A/B testing can get quite complex but let’s not forget about the basics (think back to the burger analogy). I’ll supplement this with another to illustrate that it’s important to dive into the detail when you’ve mastered the basics. Tennis is a simple sport; you hit a ball with a racket and hope the other player either hits the net or misses entirely. But if you want to improve your game, you might want to consider purchasing a new racket string. Do you go for Natural Gut? Synthetic Gut? a Kevlar string? or hybrid? For your frame, do you choose Babolat’s Aeorobeam technology Stabilizer technology? or Wilson’s Countervail blades? You get the idea. These tools can get quite complex for a relatively simple sport, but when tools are utilised, the improvement can be massive. See how this applies to A/B testing? Fortunately for you I’ve got some tools to help your testing too…

User friendly sights such as Optimizely and A/B Tasty eliminates the need for coding and only requires basic training to conduct simple A/B tests. I’ve found a fantastic “Optimizely Fundamentals” course on Lynda.com; you get a free 10 day trial which should be more than enough to get you an A/B testing king/queen with the tool. Practice the basics and you will soon be diving into the detail as you optimise your website with advanced tools; similar to the tennis player wanting to improve their game.

References

Kohavi, R., Longbotham, R., Sommerfield, D. and Henne, R.M., 2009. Controlled experiments on the web: survey and practical guide. Data mining and knowledge discovery, 18(1), pp.140-181.

Levitin, D. (2016) A field guide to lies and statistics: A Neuroscientist on how to make sense of a complex world. United Kingdom: Viking.

Martin, E. 2015, The ABCs OF A/B TESTING, ONLINE INC, WILTON.

Roy, R.K., 2001. Design of experiments using the Taguchi approach: 16 steps to product and process improvement. John Wiley & Sons.