What is CRO, conversion rate optimisation, for ecommerce?

If you run or work in an ecommerce business, you will always be looking for ways to increase your sales. So CRO or conversion rate optimisation is one of the key metrics you should care about - review and improve it. Are potential buyers leaving your online store before purchasing products? Have you looked at the potential reasons why they may be leaving and ways to improve the number of visitors who end up buying? Increasing that number of people who complete the main action, or convert, is called conversion rate optimisation. Some of the reasons why more people are not buying your products could be: product pages are loading too slowly not enough information provided about the product your ecommerce site has poor navigation information about delivery and returns costs is too confusing/difficult to find need more time to think before committing to a purchase In the video below, Edward gives an overview of CRO and talks through some examples of tests you could be running to find out how to improve your conversion rate. *This video is part of ISDI online training courses for digital professionals. Video transcription so one of the important things, if you're going to increase your return on investment of marketing campaign, is to think about how users engage with your page and this is typically called conversion rate optimisation or increasing the percentage of people who land on the page or visit the page to those that do the main action let's look at this example which is a very generic e-commerce product page as you can see the very obvious call to action, which is highlighted, is to click the Buy button to add it to cart if we get a marketing campaign to push people to page let's say the product here is some pink shoes and our campaign says buy pink shoes we are wasting money that's never going to have a positive return on investment if people out on the page and don't even like the content they don't engage with it so we need to measure very carefully what is the bounce rate  of our landing page, and the bounce rate is the percent of people who land on the page and then go away with them without doing any further action and conversion rate optimisation is really the process through which you might go to get more people to convert - in this case to click Buy so we might look at the text on the page the heading could we change the copy to make it more engaging or to make it more fitting with the users expectations so if we advertise for pink shoes this better say pink shoes somewhere in the copy the next thing we'll optimise is the image - is it appealing, is it easy to see what the product is, maybe we might add a 3d visualisation animation of the product for them to get a better feel for it and then we might experiment with a Buy button itself - how about making it bigger or make it red this might seem really trivial but you'd be amazed the difference in conversion between let's say a blue button and a red button, so altogether we can run a series of tests in the next chapter, we're going to look at a series of tests you might run to test those things but the process of doing it is conversion rate optimisation and that's really going to help you boost that return investment from any given marketing campaign Have any questions? Get in touch with our experts!   Get Social! Follow us on LinkedIn, Twitter, and Facebook and keep up-to-date with our Google Analytics insights.

2016-06-28

How to use Enhanced Ecommerce in Google Analytics to optimise product listings

Ecommerce reporting in Google Analytics is typically used to measure checkout performance or product revenue.  However, by analysing events at the top of the funnel, we can see which products need better images, descriptions or pricing to improve conversion. Space on product listing pages is a valuable commodity, and products which get users to click on them – but don’t then result in conversion – need to be removed or amended.  Equally, products that never get clicked within the list may need tweaking. Littledata ran this analysis for a UK retailer with Google Analytics Enhanced Ecommerce installed.  The result was a scatter plot of product list click-through-rate (CTR) – in this case, based on the ratio of product detail views to product listing views – versus product add-to-cart rate.  For this retailer, it was only possible to buy a product from the detail page. We identified three problem categories of product, away from the main cluster: Quick sellers: these had an excellent add-to-cart rate, but did not get enough list clicks.  Many of them were upsell items, and should be promoted as ‘you may also like this’. Poor converters: these had high click-through rates, but did not get added to cart. Either the product imaging, description or features need adjusting. Non-starters: never get clicked on within the list. Either there are incorrectly categorised, or the thumbnail/title doesn’t appeal to the audience.  They need to be amended or removed. How we did it Step 1 - Build a custom report in GA We need three metrics for each product name (or SKU) - product list views, product detail views and product add to carts - and then add 'product' as a dimension. Step 2 - Export the data into Excel Google Analytics can't do the statistical functional we need, so Excel is our favoured tool.  Pick a decent time series (we chose the last three months) and export. Step 3 - Calculate List > Detail click through This website is not capturing Product List CTR as a separate metric in GA, so we need to calculate as Product Detail Views divided by Product List Views.  However, our function will ignore products where there were less than 300 list views, where the rate is too subject to chance. Step 4 - Calculate Detail > Add to Cart rate Here we need to calculate Product Adds to Cart divided by Product Detail Views.  Again, our function will ignore products where there were less than 200 detail views. Step 5 - Exclude outliers We will use an upper and lower bound of the median +/- three standard deviations to remove improbable outliers (most likely from tracking glitches). First we calculate the median ( =MEDIAN(range) ) and the standard deviation for the population ( =STDEV.P(range) ).  Then we can write a formula to filter out all those outside of the range. Step 6 - Plot the data Using the scatter plot type, we specify List > Detail rate as the X axis and Detail > Add to Cart as the Y axis. The next step would be to weight this performance by margin contribution: some poor converters may be worth keeping because the few sales they generate are high margin. If you are interested in setting up Enhanced Ecommerce to get this kind of data or need help with marketing analytics then please get in contact.   Get Social! Follow us on LinkedIn, Twitter, and Facebook and keep up-to-date with our Google Analytics insights.

2016-03-31

9 tips for marketers using Google Analytics

Setting up Google Analytics to collect data on your website visitors’ behaviour is step one. But are you getting the insights you need? Web analytics tools like Google Analytics can provide a wealth of information about what people do on your site, but it becomes powerful when you do more than just look at trends going up or down. It’s about measuring and improving. Here are some tips on how to use your data for informed marketing decisions for your company. Make analysis a regular habit Checking analytics to evaluate website and marketing performance varies from business to business. Some do it multiple times a day or only when it’s time to do their monthly reporting or end up getting hooked on real-time analytics. Make it a regular habit to analyse your Google Analytics metrics and before you know it, you won’t need the constant reminders to do so and it'll feel less like a chore. You can start off with doing it a few times a week and if you find that there aren’t enough changes to come to any conclusions, then do it less frequently. Whilst for smaller businesses the results won’t change much hour to hour or even day to day, for the bigger businesses changes can be significant on a daily basis. Form your questions Before sifting through your Google Analytics reports, come up with a set of questions that you are looking to answer with your data. You might want to know: What are users searching for? (requires site search to be set up) Which pages are they spending the most time on? Which pages have the highest bounce rate and might need further tweaking? How are my marketing campaigns performing? Is my spending on Adwords justified? Which traffic sources bring the best converting traffic and are worth investing into? Are my call to actions working? (this is where goals come in handy) Know where to measure Think about which reports and metrics will be most suitable to answer your questions. Knowing what you're looking for will minimise the amount you spend wandering aimlessly through numerous reports hoping that you'll find something interesting. It’s said that there are over 100 standard reports available in Google Analytics, so it’s handy to know where to look. The reports are split into 4 main categories: Audience is about the users – where are they, what devices are they using, Acquisition is about how users get to your site – how are your campaigns performing, where do they come from Behaviour is about user interaction with your site – which landing pages get the highest traffic, which pages have the highest bounce rate Conversions is about users completing certain actions (requires further setup to get the most out the reports) – which goals did they complete, what is their shopping and checkout behaviour Pages with high page views and bounces / exit rate Check how your individual pages are performing in All Pages and Landing Pages reports (under Behaviour > Site Content). If your page is getting a lot of page views and has a high bounce / exit rate, then whilst it might be a valuable or attractive piece of content it’s not doing a great job at getting your users to another page. Can you provide some other relevant content on that page? Link to them where appropriate. This will help improve the visitor journey through the site and reduce the bounce rate. Know your user journeys You can use Google Analytics flow reports to view which paths users take through your site and where they drop off. Evaluate the pages with the biggest drop offs  - can you improve these pages to encourage users continue their journey? You've put a lot of work into the pages that are meant to convert your site visitors, but it's a waste of all that effort if your journey to the converting page doesn't work. Goal flow report is especially handy for seeing users' paths towards the goals you have set up. Not sure how to set up a goal funnel? Here's how. Segment your users Use Google Analytics segments to view and analyse a separate subset of user data. You could view your reports for users from a specific location, eg Spain, or with a specific device, eg Apple iPad, or by certain behaviour, eg made a purchase. Check out Google's guidance on using segments. Evaluate your tagged campaigns Custom campaign tracking is important for organising your campaigns so you can review the performance effectively. If you're not tagging your campaigns yet, check out our blog post on how to tag your campaigns. Share findings with the team It’s great if you get into the habit of reviewing Google Analytics data on a regular basis to inform your actions. What's even better is if you create a team culture where you share findings with each other. You can email around individual reports, share insight at team meetings, set up custom alerts or sign up to our web-based tool to do that for you. For those less geeky or knowledgeable about data, make sure you translate the findings into plain English statements (PS. our tool already does that too). Continuos improvement When Dave Brailsford became the head of British Cycling, he implemented the concept of marginal gains within cycling. He believed that by breaking up the process of competing and improving every step by 1%, they would see a big improvement in their team. And he was right. All the small changes accumulated into a massive performance boost, and Team GB surpassed everyone’s expectations by going on to some big wins at Olympics and Tour de France.  This can apply to many other areas as well - customer satisfaction, improving service quality, doing minor updates to marketing campaigns. Rather than focussing on one big improvement and spending weeks or months on it, before even knowing if it'll work, look at the potential small changes you could make. You will spot much more quickly which of these changes are of benefit and which are not. There's a lot of information stored in your Google Analytics, when used correctly and regularly you will start getting the insight you need to guide your marketing efforts. Suggestions above will help you do just that. Something else on your mind? Let us know in the comments below or get in touch!   Images: Courtesy of Suriya Kankliang, pannawat at FreeDigitalPhotos.net

2016-03-17

New in Littledata: tailored tips, new reports and more

We released the last updates just a few weeks back, but we've done it again. The new improvements will help you get more out of your reports and make your analysis more efficient, but if you've got any other requests or feedback, don't hesitate to let us know. So here's what we've done. Report improvements Discover where you need to improve Tips reports identify the gaps in your analytics setup and suggest fixes or improvements to boost your tracking. We are working on bringing you more of these tailored tips but we need to know what you're trying to achieve to get these right. By updating your report preferences in the subscription settings, you will start getting personalised suggestions and we will use this information for other future tailored reports. You can get to your subscription settings by clicking on the cog icon in the header. See more detail on your referrals It's important to stay on top of your website traffic changes with minimum time waste. This is why we developed Littledata software in the first place. Now we have added extra information to your referrals reports so you can immediately see which sources had the biggest increase or decrease. You will also see the option to pick the type of reports you want to get. Just click on the 'Yes please' button at the bottom of the report to see your choices for customisation. New monthly report So far you've been getting reports that look at the changes in your Google Analytics data on a daily and weekly basis. We've had a lot of requests for monthly comparison reports instead, so we've added these to your feed. Just like your daily and weekly reports, you can spot the new monthly ones by the time tag. Benchmark your website performance It has always been difficult to get a hold of benchmark data to find out how you’re performing against others. You often have to spend a lot of time crawling through the internet to find anything remotely useful. With our new website performance benchmarks we are changing that. Now you can compare your engagement metrics to other websites. You’ll be able to tell whether you need to focus on improving your bounce rate from a particular source, or page load for example.   Feel free to ask questions or send us your comments either below or via the Intercom Messenger available when you're logged in.   Further reading: Under the hood of Littledata

2016-03-14

How to use the lookup table variable in Google Tag Manager

A lookup table in Google Tag Manager makes it much simpler to manage lots of values in your tracking setup. It can drastically reduce the number of tags required and turn your messy GTM into a neat environment. It's especially useful with larger setups where you have multiple tracking requirements and flexible to accommodate new tracking needs as they arise. You can easily add or remove values from your lookup tables, and not worry about having to change any codes. The lookup table variable allows you to define a set of key-value pairs where the output variable (the value that you are sending to Google Analytics) is linked to the identifier (the key). It works like this: When [input variable] equals to  _______, set [this output variable] to_______. For example, you could use the lookup table for: Assigning different Google Analytics property IDs for various domains/hostnames, eg. when [website hostname] equals to littledata.co.uk, set [property ID] to UA-010101 (see example below) Setting different pixel or conversions IDs for different country websites, eg when [website country code] equals to 2, set [pixel ID] to 88779 (requires having website country code variable defined) Defining your event categories, actions and labels (see example below) Remember! There’s no limit to how many values you can have in the lookup table, but the fields are case sensitive. So if you have multiple capitalisations of some input, then include all of them in the lookup table and assign the same output for each. I have previously explained setting up the tracking of user actions as events in GTM, but when you need to track multiple events, one tag just doesn't cut it anymore. And instead of creating several tags to cover each event or action, here's how you would create the lookup table to cover multiple values in one place. Creating lookup table variable for event parameters In the Littledata software interface, you get an option to switch between different report types or view them all. I want to track when people click on different report types, so instead of creating 5 different tags for each user action, I will set up a lookup table to cover all of them in one place. But firstly I need to know which variable to use as the input. You can only have one type of input variable per the lookup table so you want to pick a variable type that applies to each (ideally). For this, I will check how each report type option has been set up in the code by inspecting the element (inspect/inspect element depending on the browser you're using and usually accessible via right click). Here's how each report type has been set up: <a href="/report-list/m2i4MnmXcewDSzZ3c/all" class="current" id="ga-all">All <span class="count">120</span></a> <a href="/report-list/m2i4MnmXcewDSzZ3c/trends" class="" id="ga-trends">Trends <span class="count">80</span></a> <a href="/report-list/m2i4MnmXcewDSzZ3c/pages" class="" id="ga-pages">Pages <span class="count">37</span></a> <a href="/report-list/m2i4MnmXcewDSzZ3c/tips" class="" id="ga-tips">Tips <span class="count">3</span></a> <a href="/report-list/m2i4MnmXcewDSzZ3c/benchmark" class="" id="ga-benchmark">Benchmark <span class="count">0</span></a> Looking at the above, I can see that each report type has a unique ID - here that's the best one to use. Now to set this up, go to Variables, click ‘New’ and select 'Lookup Table' as your variable type. For the input variable, I will use {{Click ID}} as explained above, but you, of course, use whatever unique identifier you have available. For your output, you want to define the event action you are going to send to the Events report in Google Analytics. Should you set the default value? You can set a default value for the output when there is no match found in your table. With the event tracking, I sometimes find it useful to enable to identify if I set up my tag correctly. If my trigger ends up being too broad, the default value option will pick up additional values not defined in the table. I will then see these values in Google Analytics reports and this way I can tidy up the trigger to be more accurate. So this is what your variable should look like now. Click ‘Create Variable’ and there you have it. In your GA event tag, the newly created variable would look like this. Other uses Multiple Google Analytics properties If you have a single GTM container installed on multiple domains but you're tracking them across different Google Analytics properties, you want to ensure that you're sending the data to the correct one. Instead of having multiple variables to store different property IDs, you can have them all neatly in the same table defined by the hostname. This way any tracking activity on each site will go to its own dedicated property. Excluding test or other data If you want to make sure that any data outside of your main site goes to a test or other Google Analytics property, you can do so by setting the default value. The default value is the output that is not found in the table. With this setup, any activity tracked on www.mainsite.com goes to property ID UA-121212. If the activity wasn't on www.mainsite.com, then it sent to property ID UA-121212-2. Use lookup tables for something else? Confused? Get in touch or comment below!

2016-03-09

How to set up event tracking in Google Tag Manager

Events in Google Analytics are important for understanding how people interact with your website. They give you additional insight into their behaviour and how effective your pages are for leading users towards a conversion. With event tracking you could see how many users clicked on a button or played a video, scrolled down a page or clicked on your contact and social media icons. I mostly use Google Tag Manager (GTM) for analytics setup so I will show how to set up event tracking for clicks on buttons with GTM. Instead of hard coding events in the code, GTM allows you to create, test and amend tags within its interface. Before you go ahead creating your event tags, make sure your built-in pages and clicks variables are enabled. This will avoid you having to go back and forth between different sections. The setup below covers only one action - a click on a specific button - but if you have multiple actions to track, then look into implementing a lookup table variable. Tracking button clicks Here's my scenario. I want to track our BENCHMARK YOUR SITE button that allows users to sign up to our free software plan and get benchmarked against competitors.   And here's how to set it up. 1. Create a tag It will be a Universal Analytics tag type where tracking ID is a constant string variable (you need to create this variable before using it) and track type 'Event'. Think of your event tracking parameters as a way to organise the events into a hierarchy: Category – the main aim of the button or its placement Action – what the user clicked or the action Label – provides additional information like on what page the button was clicked or the outbound link they clicked on Value – if you have a numerical value to set for your click (not in my case tho) In my example, the category is ‘Get started’ because we have a number of similar buttons across the site with the same purpose to get the user started with the signup, so all of them have the same event category. For action, I specify the type of button that was clicked on so I can compare how these different buttons perform - 'Benchmark your site' in this case. My event label is the {{Page Path}} where they clicked on the button. The buttons take the user to the same place so I’m more interested in which pages these buttons were clicked on. Alternatively, if you have buttons that take people to different URLs you might want to track that instead. Is it a non-interaction hit? This is an important one to keep in mind. By default this is set to False. If you don’t want this event to impact your bounce rate, then change it to True, which you would do if the click or action didn’t take the user to the new page, or if you didn't want it to be included in your bounce rate calculations. Now click 'Continue' to go to the trigger setup. 2. Create a trigger Trigger is like a rule that allows you to tell the tag, ie specify the conditions, when it should fire. Under 'Fire On' select ‘Click’ as your trigger type and then ‘New’. For configuring the trigger, you have a choice between two types: Just Links – use this when the target is a link or anchor tag <a> All Elements – use this when the target is any other element that’s not a link To determine what’s best for your purposes you need to have a look at how your button is set up. You can do this by selecting ‘inspect element’ or simply ‘inspect’ depending on what browser you’re using. It’s usually available when you right click on the button or element.   Our button has been set up the following way: <a href="https://littledata.uk/signup" class="btn btn-ltd btn-green">benchmark your site</a> It has a link so I will use 'Just Links' for targets and I have a choice between three elements to use in further configuration: https://littledata.uk/signup as click url btn btn-ltd btn-green as click class benchmark your site as click text It is best to use a unique condition if you can. This way, if similar class or click url gets reused in other parts of the website you don't have to go back to this trigger to update it. With 'Just Links' you will get additional configuration options: Wait for tags - delays opening of links until all other tags have fired or the wait time has lapsed, whichever happens first Check validation - fires the tag only when opening the link was a valid action, without the tag will fire whenever the user clicks on the button/link Enable when - this options is shown only when either of the above is ticked so you can be specific about where you want the trigger to be active If you want the trigger to listen to the interactions on all pages, then set that section to be  URL or Page Path matches regex .*. (without that very last full stop - that one's for the sentence) In my case, I only want it to work on benchmark pages and all of them start with /benchmark/. The very last step in trigger setup is specifying on which actions or clicks the tag should fire. As said above, I'm using the button's click class here. All done? This is what your tag should now look like. Click 'Create Tag'. 3. Test Test your tag in GTM's preview mode by checking two things: the tag fires in the preview interface, and the tag is seen in Google Analytics real time view under 'Events' with the event parameters you specified   I hope you got on with the setup above just fine, but if you have questions or clarifications, feel free to ask below.   Further reading: Know who converts on your site with Google Analytics goals Using lookup table variable in Google Tag Manager Intro to Google Tag Manager's key concepts and terminology Image: Courtesy of suphakit73 at FreeDigitalPhotos.net  

2016-03-02

SEIS support covers over 100% of your startup investment risk

Until recently I hadn't understood how generous the Seed Enterprise Investment Scheme is for investors in early-stage companies. Investors can put up to £100k in qualifying companies, as long as they don't control more than 30% of the SEIS company. There are three overlapping benefits which mean you can recoup over 100% of your investment in tax offset if the companies goes bust, and get a 5x boost to the value of your initial investment if all goes well.  It sounds too good to be true, so use your allowance while it is still open! Let's assume that you are an additional rate (45%) tax payer, and want to invest £10,000 of capital gains into an SEIS company. What happens if that company eventually goes bust? A. Reinvestment relief Firstly you get a 50% reduction in the capital gains tax bill from gain reinvested.  If you realised a gain of at least £10k over and above the capital gains tax allowance from selling shares or property, then you can reclaim the tax on the amount you reinvest in the SEIS company.  At the 2014/2015 higher rate of 28% that is: + £2,800 B. Income tax relief Next you can write 50% of your £10k investment off against your income tax bill from this year or last - even if you didn't directly use that income to invest in the SEIS company. +£5,000 C. Loss relief If the company goes bust, then you can write a further 45% (your marginal tax rate) in the year you claim against your income tax bill. 45% times the £5,000 of investment the tax payer didn't originally fund. +£2,250   So of that £10k you have already recouped £2,800 + £5,000 + £2,250 = £10,050 from HMRC. Leaving you with a small gain to cover the inconvenience. But look on the bright side! What if the company sells for double the value in a few years' time? This time you still get benefits A & B, but also keep the proceeds free of capital gains tax. So you put in £10k, but take £7,800 back off your tax bill, leaving you with £2,200 net exposure.  When you sell the shares for £20k, you have multiplied your capital at risk 9 times An investment in an equivalent non-SEIS company would have yielded £20k, less capital gains tax of £2,800 = £17,200 (1.7x your investment) So you get more than five times the net gain from the SEIS investment.  

2016-02-25

3 steps to great email customer support

As a consumer brand, is there a better way of getting customers to refer you business than offering excellent customer support? My inbox this afternoon showed two polar opposites of handling support by email and illustrated what great support looks like. I can sum up the differences: Ditch the "you're in a queue" email Really listen to the customer Offer further advice Ditch the "you're in a queue" email My depressing email exchange with Swiss Airlines starts when I tried to complain about the £4.50 credit card charge. I would normally never pay it, but their debit card payment route was broken, so to book the flight I had no choice. Dear customer, thank you for your message. We will get back to you as soon as possible. The response time may vary depending on the amount of research required. Please do not reply to this E-Mail. Use for your feedback our page: www.swiss.com/contacts We thank you for your understanding. Yours sincerely, Swiss International Air Lines Ltd. Let's unpack the sheer hostility of this: "thank you for your message" = we care so little we couldn't be bothered to add a capital letter "as soon as possible" = nor do we have enough staff to answer today "Please do not reply to this E-Mail" = we can't even be bothered to install a smart ticketing system Really it would be better not to send me an auto-response at all - just get back to me when a human is ready. Let's compare that with an email I get from TransferWise, which was my good experience of the day. At first glance, this looks like an automated response, but then I realise it's signed by a real person - and they actually want me to reply to the email. TransferWise are having to deal with genuinely onerous FCA anti-money laundering rules - and offering a helpful way to get around it. Really listen to the customer The Swiss conversation goes downhill from there. OK, I'm a bit smart Alec about the transaction fee - but it's a well known scam. On 24 Feb 2016, at 05:51, contactus@swiss.com wrote: Dear Mr. Upton, Thank you for writing to us with regards to your query and we apologizes for the inconvenience caused. We would like to inform you that GBP4.50 is the fee charged directly from the bank/bank fee. Therefore, we cannot grant a refund with regards to the above mentioned fees. We trust the above information will be of assistance and are available to assist you with any further questions at any time. Thank you for choosing SWISS and we wish you a pleasant day further. Kind regards, Miriama Consultant Customer Travel Services / R1S ----- From: Edward Upton [mailto:edward@edwardupton.com] Dear Miriama, That is absolutely untrue. MasterCard charges you 0.3% for the transaction, which in this case is 51p https://www.mastercard.us/en-us/about-mastercard/what-we-do/interchange.html So please can you refund me GBP 4? regards, Edward Upton ----- From: contactus@swiss.com Dear Mr. Upton, Thank you for writing to us. We have reviewed your request regarding your reservation. Please note that in regards to your request we will not be able ot refund the OPC. Please note this (GBP4.50) is a charge placed by the credit card company and it applies as per the point of commencement of your ticket. We hope this information is useful. Please do let us know if you need additional information. Thank you for choosing SWISS. Kind Regards, Alexander Consultant Customer Travel Services / R1S This feels like someone has cut and pasted from a standard response list. It's robotic. And given that the original issue was actually about their website being broken, there is a total lack of empathy for the issue - just some 'apologizes' (sic). Offer further advice Often companies have to say no to refunds and extra requests, but at least be gracious. And sometimes the company can offer you something that benefits both parties: a guide to how to avoid needing to email in the future. Here is the exemplary reply from Transferwise Hi Edward, I hope you’re doing well! Thank you for getting back to us, and confirming that we can change the name on the payment ###### to your personal. I shall quickly pass this on to my colleagues, who are able to make the change and proceed with the transfer. As soon as the payment is sent out from our end, we shall send you a confirmation e-mail, like always. All you need to do is check your inbox every now and then.:) Just in case, I will explain how you can choose to use both your personal and business profiles on TransferWise. Once you log in to your TransferWise account, on the upper right corner you should see a logo (like a man in a circle). When you click on the logo, you should see: Use as Edward Upton Use as Littledata Consulting Ltd Therefore, if you want to set up a personal payment, and you’re planning to send money from your personal bank account, please make sure that “Use as Edward Upton” is ticked. And if you’re planning to make a business payment and send money from your business bank account, please make sure to choose the second option. If anything was left unclear or you would need help with something else, please don’t hesitate to get back to us. We are always happy if we can help! I hope you have a lovely day, Eliisa, TransferWise Support Which company do you think I'll recommend in the future? Comment below!

2016-02-25

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