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Optimisation & Personalisation Specialist
€80 - €95 per hour
This could be the role which defines your career going forwards, as you'd be joining an eCommerce brand with a reputation for cutting edge work.
HOW TO APPLY
Please register your interest by sending your CV via the Apply link on this page.
For further details or to enquire about other roles, please contact Dan Lewis at Harnham.
IBM, Coremetrics, Google Analytics, GA, Omniture, SiteCatalyst, Adobe Analytics, Analyst, Web, Digital, Online, Website, Financial Services, Finance, A/B, Test, Split, Multivariate, MVT, Tracking, Code, Tagging, Tags, Insight, Client, Agency, Management, Strategy, CRO, Conversion, Optimisation
£40000 - £60000 per annum
Devise and implement end-to-end optimisation strategy for a range of high-end clients
£70000 - £75000 per annum
If you are a UX expert and have lead teams in this area this could be a great step up in your career.
£30000 - £50000 per annum
Analyse high-velocity AB and MV tests at a digital media start-up in this CRO Analyst position
£30000 - £37000 per annum
Flexible, Sociable agency who offer next to none training & progression opportunities in search of a CRO Analyst.
With over 10 years experience working solely in the Data & Analytics sector our consultants are able to offer detailed insights into the industry.
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It’s that time of year again. Decorations are going up, the temperature is dropping daily, and the year’s biggest shopping weekend is upon us. Black Friday and Cyber Monday may have started stateside, but they’re now a global phenomenon. This year, in the UK alone, shoppers are expended to spend £8.57 billion over the four-day weekend. But, for retailers, this mega-event means more than a cash injection. In the world of Data, insights gained from shopping and spending habits during this period can dictate their product and pricing strategies for the next twelve months. So what is it, exactly, that we can stand to learn from the Black Friday weekend? THE GHOST OF BLACK FRIDAY PAST There are a few interesting takeaways from 2018’s Black Friday weekend that will likely impact what we see this year. Firstly, and perhaps unsurprisingly given that it’s a few years since the event has become omnipresent, spending only increased about half as much as initially predicted. There are a number of reasons for this, but cynicism plays a central role. More and more, consumers are viewing Black Friday deals with an element of suspicion and questioning whether the discounts are as good as they’re promoted to be. This, combined with other major annual retail events, such as Amazon’s Prime Day, means that this weekend no longer has the clout it once did. However, 2018 also saw marketers doing more to stand out against the competition. Many businesses have moved away from traditional in-your-face sales messaging and some are even limiting their Black Friday deals to subscribers and members. By taking this approach, their sales stand out from the mass market and can help maintain a level of exclusivity that could be jeopardised by excessive discounts. In addition to branding, marketers making the most of retargeting saw an even greater uplift in sale. Particularly when it came to the use of apps, those in the UK using retargeting saw a 50% larger revenue uplift than those who didn’t. So, having reviewed last year’s Data; what should businesses be doing this year in order to stand out? GETTING BLACK FRIDAY-READY WITH DATA Businesses preparing for Black Friday need to take into account a number of considerations involving both Marketing and Pricing. For the latter, Data and Predictive Analytics play a huge role in determining what items should go on sale, and what their price should be. Far from just being based on gut instinct or word-of-mouth, algorithms derived from Advanced Analytics inform Machine Learning models that determine what should be on sale, and for how much. These take into account not only how many of each discounted product need to be sold to produce the right ROI, but also what prices and sales should be for the rest of the year in order to make the sale financially viable. In terms of Marketing, Deep Learning techniques can be used to accurately predict Customer Behaviour and purchases. These predictions can then reveal which customers are likely to spend the most over the weekend, and which are likely to make minimal purchases. Marketers can then, in the lead up to Black Friday, target relevant messaging to each audience whether it be “get all you Christmas shopping in our sale” or “treat yourself to a one-off item”. By carefully analysing the Data they have available and reviewing the successes and failures of their Black Friday events, businesses can generate greater customer loyalty and improve their sales year-round. If you’re looking to build out your Marketing Analytics team or take the next step in your career, we can help. Take a look at our latest opportunities or get in touch with one of our expert consultants to find out more.
28. November 2019
Web Analytics have long been used to help companies understand their customers’ online behaviour, extracting and interrogating an abundance of information; from time spent on pages to bounce rates and conversion rates. Having provided a lot of insight as to what customer are doing online, these techniques have been less useful for understanding why they do it. This is where psychology comes in. As the why of Web Analytics becomes more and more important, with companies always looking ways to edge out the competition, there are more links to psychological principles than you might expect. Of course, traditional Web Analytics and metrics remain very important. However, what psychology can do is help us speculate as to why customers may be behaving the way they do and, by doing so, allow businesses to make more informed changes to their websites, or conduct more conscious testing. Without directly asking we will never know the real reason behind customer’s actions, but we can use a number of established psychological constructs to make well informed assumptions. We can then work this backwards and use these constructs to make changes to our sites that will fall in line with these assumptions in order to convert more customers. Familiarity People tend to favour that which they are familiar with, whether it be items of clothing that match their preferred style or holidays like ones they have been on before. A customer visiting a page to find a series of unfamiliar products is more likely to leave without making a purchase. This is why personalisation is important; it gets rid of unnecessary information and leaves the user with products they are more likely to want. By working backwards, businesses can personalise their sites to each individual customer. If you’ve ever bought an item of clothing from an online shop only to be shown a number of similar items the next time you log on, you’ll know what I’m talking about. The thinking is that, as these items are more familiar to you, you’ll be more likely to either purchase them, or remain on the site to purchase something else. Social Proof Research into social proof has shown psychologists that the more people who reinforce a certain concept, the more likely it is that other individuals will perceive it as correct. This heuristic is used widely by companies like Just Eat and Deliveroo who allow customers to leave comments about their restaurants and give them a star rating. It is much more likely that conversion rate will be higher on restaurants with better reviews as the rating allows the customer to make a quick judgments on its quality. Scarcity This is a cognitive bias where humans put more value on things that are scarce over those that are in abundance. If one site is showing a product with no indication to the quantity left but another company is showing a similar product where there are only three left, the customer is more likely to convert on the second site. Where an item is nearly unavailable, this suggests a number of things; it is more valuable and it is desired by more people (social proof) etc. Companies like Amazon and Asos use this technique by showing visitors when an item is low in stock or even showing how few are left, giving them an edge on conversion over their competitors. Web Analysts and CRO professionals should take note of user psychology and start to implement it in their day to day practice. In fact, some might be already without even knowing the fundamentals of the psychology behind these techniques. Applying the above techniques and testing these ideas could produce a boost in conversion that simple changes to user experience, like changing the position of the checkout basket, aren’t providing. A number of businesses are now looking for Analysts who can explain why customers are behaving in a certain way and tell a story with the Data, rather than just explaining what was found. Finding someone with this deeper understanding of user psychology has therefore an integral part to many hiring processes. By looking into this area, candidates are likely to increase their chances of securing the role they want. Whether you’re looking to expand your Web Analytics function or want to take the next step in your career, we can help. Take a look at our latest opportunities or get in touch with one of our expert consultants to find out more.
03. October 2019