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Data is probably the biggest buzzword in modern marketing but actually turning data into profitable business decisions is something of a science. In this bitesize blog, we explain what data science is in simple terms and what it can do for marketers.

What is it?

Data science is all about extracting valuable insights from data – the kind of insights you can turn into business and marketing decisions that improve performance. If you’re looking to turn data into higher profit margins, increased lead generation, higher search rankings or a more efficient paid advertising strategy, data science is the way to do it.

Simply collecting data does nothing by itself. To make a real impact on your marketing efforts, you need to start by identifying which data points hold the information you need, create models for collecting that data effectively and find a way to present all of that information in a way that allows you to extract insights (graphics, charts, etc.).

Data science provides the theory and practices you need to achieve this.

What can data science do for marketers?

In today’s data-driven marketing environment, it’s not much of an exaggeration to say everything starts and ends with data science: Data collection, algorithm development and deployment, data visualisation, machine learning, analytics and so on.

We can’t cover everything it has to offer for marketers in a bitesize blog but we can list some practical examples of what you can achieve to give you a good idea:

The list goes on and you can find out more about the amazing things we’re doing by visiting our blog. Or, if you have any questions, just call us on 023 9283 0281.

The post Bitesize blog: What is data science? appeared first on Vertical Leap.

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It is with a heavy heart that we share with you the news that on Sunday the 12th May, Vertical Leap’s Services Director, Steve Masters, passed away.

Earlier this year Steve had been diagnosed with terminal cancer and despite a great deal of uncertainty about what that meant for his long term prognosis, Steve dealt with the news in his typical calm and stoic nature, making sure that all of those around him were OK. 

He maintained his sense of humor and work ethic; and as was typical of Steve, chose to embrace the situation and find the good in it.  There are no adequate words to describe how much we and his customers will miss him. 

Below are links to Steve’s book he wrote about his experience with cancer; and also to a Just Giving page Steve created to provide support for his family.

If you have any questions about this or anything else, please don’t hesitate to contact us.

The post Remembering Steve Masters appeared first on Vertical Leap.

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This week is Mental Health Awareness Week in the UK and we wanted to share with you some of the things we’ve recently implemented at Vertical Leap.

We are big believers that companies have a really important role to play when it comes to the mental health of their employees – after all, most of us spend at least eight or nine hours a day at work. And, given that some of the stresses in our lives are caused by things happening at work, anything that we can do as a collective to help in this area is likely to have a big impact.

We wanted to create an environment where people felt they could talk more openly about their mental health without fear of being judged. If someone is suffering from depression or anxiety, for example, it’s important that they feel they can tell someone so that we can do our best to understand and try to help.

We also wanted to raise awareness of mental health conditions – what are the symptoms? What does it feel like? What can people around you do to help? By increasing our understanding, we hoped to develop more empathy and compassion towards other people. This point is really important; if someone seems down in the office, quiet, plugged into their earphones all day, not joining in… what you say to them and how you say it can make a real difference to someone who might be going through a really tough time.

So here’s what we did.

Monthly mental wellbeing sessions

The first thing we identified was that we didn’t have a proper opportunity to talk about mental health. Sure, you might ask someone how they’re doing whilst making a cup of tea, but it’s very unlikely someone will feel comfortable opening up about how they’re feeling in that situation.

What we needed was a designated time and place where we could have an open and honest conversation – somewhere people would feel encouraged to talk as opposed to worrying about how others will perceive them. So we set up a mental wellbeing calendar for the year with an hour-long session every month. We decided to focus on one subject in each session, for example:

January – Stress
February – Sleep
March – Grief
April – Depression
May – Anxiety

…and so on.

This means that employees can see in advance what we’ll be talking about and choose which ones they want to come along to.

What happens in these sessions?

Our sessions tend to look like something like this:

  • I introduce the topic, show some research and stats
  • A couple of volunteers might talk about their experiences to allow everyone to settle into the subject and take the pressure off people feeling that they need to speak straight away
  • Open chat with everyone (no pressure to contribute, some people just prefer to listen and that’s perfectly fine)

Just to point out here, I am not a qualified mental health professional (I’m a marketer) and we don’t have one in the sessions. I see my role as ‘making sure that the conversation is happening and you don’t need to be an expert to do that. The advice comes from everyone who is in the session – we are just a bunch of people trying to help each other.

Of course, if you have budget to invite a professional to your sessions then this would be helpful especially if you want to talk about more complex mental health issues such as schizophrenia and self harm where expert advice is quite critical. But if you don’t have budget to do this, don’t let it stop you. Maybe just restrict the topics to ones such as depression, stress, anxiety which many people suffer from and often have really helpful tips and advice they can share with the group.

What do we talk about?

There is no set structure for our sessions but we tend to ask each other things like:

  • How does it feel?
  • What causes it?
  • What techniques do you use?
  • How can we spot the signs in others?
  • What can we/the company do to help?
  • What’s your top tip? (these are used for handouts)
Reaching the wider company

Not everyone wants to come along to these sessions and that’s absolutely fine. However, it’s really important that we still try to connect with these people and make sure that they have access to the knowledge we’ve shared. So, we create a round-up of advice and tips, print them out and put one on every desk. That way, the information is there if they need it – you never know, something might just catch their eye that helps them with something they’re dealing with.

Handout from our ‘Stress’ wellbeing session

A point worth noting here: One of our employees has told me that he suffers from depression and anxiety. He prefers to keep this private and therefore has no intention of coming to any of the sessions but he said just the fact that they’re running is brilliant and means a lot to him. It is great to hear that the impact the sessions have goes beyond those that attend. It’s also about the message that it sends to everyone who works here.

Mental health survey

We have two main objectives with our mental wellbeing sessions.

  1. Remove the stigma that surrounds mental health by having open and honest conversations about it.
  2. Improve the mental health of our colleagues.

In order to achieve the second point, we needed to understand where we were as a company with our mental health. That would give us a starting point upon which to build.

So we carried out a survey – you could put your name or team or choose to leave it anonymous (happy to share the questions with you if you’re interested in doing your own). The results were quite eye-opening – so many more people than we imagined were dealing with depression, anxiety, sadness etc. And, the number of people who thought they “might be but weren’t sure” was also really interesting.

We also asked for suggestions about how the company could help improve mental wellbeing and we now have a HUGE pot of ideas to take on board. This was such a valuable exercise that I would highly recommend.

Wellbeing comms channel

Whilst our monthly sessions are great, we were keen to keep mental health at the forefront of everyone’s minds on a more regular basis. So we set up a “Wellbeing” channel on Microsoft Teams where we can post content, share apps, books, recipes and so on.

Again, this is a great way of reaching anyone who doesn’t come along to the sessions and a constant reminder that as a group of people, we care about the mental health of the people we work with.

So that’s where we’re at since we started the initiative in January – we’ve come a long way in just five months! Our understanding of mental health is getting better all the time, we’re talking about it much more openly and hopefully developing more compassion and empathy towards others which can only be a good thing 🙂

The post How and why we set up a mental wellbeing initiative at Vertical Leap appeared first on Vertical Leap.

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Knowing how different marketing channels work together to drive conversions and sales is key for marketers, and there are several attribution models available to help you examine your data from one angle or another.

But that array of options often creates more confusion, rather than insights. Which attribution models give marketers the best picture? That’s the question we’ll tackle in this post, by analysing the pros and cons of the 6 main attribution models.

What are attribution models?

An attribution model is a set of rules an analytics platform uses to map conversions and sales to respective touchpoints in a customer’s journey. People come to your website through different channels:

  • Paid and organic search
  • Referral links
  • Affiliate links
  • Social media networks
  • Emails
  • Direct URLs and custom campaigns you’ve set up.

Attribution modelling shows you which ones bring in the most sales and which ones assist conversions – the marketing actions/channels that contributed to sealing the deal. But being a descriptive analytics tool, GA can only tell you how users interact with your website and other properties before converting.

It prescribes the right actions or predicts how conversions will change if you optimise a certain channel – it’s your job to properly capture and interpret all the available data. Arguably, that’s the hardest part of any marketer’s job. But that’s where data science can help.

There are several attribution models you can consider:

1. The last interaction attribution model

The credit for sale (conversion) is assigned to the last platform or channel that a user came from before converting.

Example: you are hosting a webinar and place a link to your product in the description box. Out of 100 attendants, 10 clicked that link and signed up for your tool. According to the last interaction attribution model, 10 sales will be credited straight to the webinar platform (referral traffic).

Sensing a fallacy here? This model does not account for all the other marketing activities you’ve used to generate the buzz around your webinar – that aggressive email campaign you did; the paid social media promotion and all the blog posts you’ve published to gather a warmed up, relevant audience for your event. The last attribution model does not account for all the other touchpoints a user probably had before converting.

  • Relatively easy-to-set up. Most analytics tools use this attribution model as default.
  • Delivers straightforward insights into cost-per-lead metrics.
  • Provides data into what’s driving the bottom of the funnel, one step away from conversion.
  • Tracks only the last steps in the buyer’s journey.
  • Gives you limited visibility into assisted conversions; diminishes the role of other mediums in your campaign.
  • Can leave you with a strong impression that only a few (or one) of your marketing channels work, while others show zero conversions (even if that’s not the case).
2. The first interaction attribution model

All the credit goes to the first touchpoint a customer had with your brand. You assume that once the person is there, nothing else can push them towards or derail from converting.

Example: Tim googled your blog post. Two weeks later, he clicked a display ad or typed in the website URL directly and placed an order. Organic search will get full credit. Other actions are not considered.  

  • Simple and straightforward way of measuring demand generation.
  • Good choice for businesses using a few (under five) marketing channels to determine which ones drive the most brand awareness and top-of-the-funnel customers.
  • Suitable for companies with short buying cycles and sales funnels designed for immediate conversions – (saw and purchased).
  • Similarly to the previous model – you don’t get insights about assisted conversions/other channels.
  • Limited CRO: without knowing what exactly impacted the conversion, you have little room for experiments and optimisation.
  • Unsuitable for measuring the results of omnichannel digital marketing campaigns or for companies with long sales cycles.
3. Linear attribution model

This one accounts for every touchpoint a customer had with your business before converting. All the involved channels receive equal credit for each sale (e.g. 50%-50% or 25%-25%-25%-25%).

Example: Jane takes the time to interact with your brand before converting. She stumbles on your blog post (organic 25%) + clicks on your tweets (social media 25%) + checks your email newsletter (25%) + types your website URL directly and buys a subscription (Direct 25%).

  • Provides visibility into every channel that drove conversions. An easy gateway to multi-touch attribution analysis.
  • Allows you to optimise different campaigns/channels, matching different steps of the customer journey.
  • Not every channel has equal impact on conversions. Yet, this model assigns equal credit to low-value touchpoints (e.g. social media clicks) and high-value touchpoints (e.g. pricing requests). You cannot determine what channels/activities work best and where to pour more budget.
4. Position based attribution model

In this case, different touchpoints get fairer “weights” based on their position in the user’s journey. The first and last touch points receive a 40% credit allocation as they are deemed more important than what happened in the interim.

Example: Leo found your brand on Instagram (40% social media). He subscribed to your newsletter and clicked a link (20% email). Later he placed an order through an affiliate link shared by his favourite blogger (40% affiliate).

  • A more realistic representation of modern customer journeys. Every touchpoint is credited to some extent. You can also determine the two main channels (first and last) for further optimisation.
  • Over-emphasises the importance of the two touchpoints, while neglecting others. The percentage allocation may not realistically represent your business sales cycle and the value of individual campaigns. Should a generic email newsletter be given more credit than a niche Facebook retargeting campaign?
5. Time decay attribution model

Touchpoints taking place closest in time to sale/conversion receive the most credit. In other words, the first click has the least value, the last one reigns supreme. But every action in between is measured as well. For additional accuracy, you can add a half-life for a certain decay. The touchpoint at that period will receive 50% of the credit of that final touchpoint.

Example: Lisa navigated to your website via a search ad (10%). Later she found your website again by googling it (15%), subscribed to your newsletter, and clicked back just in time for sales (25%). But her shoe size was not in stock, so she came back directly a few days later (50%).

  • More accurate weights are given to every channel/interaction that drove conversion with most credit assigned to the last action that “sealed the deal”.
  • Helps optimising conversions and assisted conversions. Well suited for businesses with long sales cycles.
  • Fails to acknowledge the importance of brand awareness campaigns that placed your brand in the customers’ spotlight.
  • Due to being linear, this model does not fairly highlight the more important touchpoints e.g. webinars and email marketing could have more impact on conversions earlier in the journey than that final conversion through a direct link.
6. Custom attribution modelling

The proposed attribution models can be further customised with additional rules and benchmarked against one another, for example by using the Google Model Comparison Tool. Custom modelling gives you more room for reconciling the analytics with the actual customer journeys. However, it will still assign the same predetermined weights to different channels.

A better way…

So if every model is flawed in one way or another and does not provide a full picture, what’s a business to do? The answer is to use a data-driven attribution model.

Unlike others, this model leverages actual data from your account to generate a custom model, personalised to your business, for determining various touchpoints throughout the entire customer journey and assigning custom credit weights to them.

This all sounds great but, unfortunately, Google only offers it to Google Analytics 360 customers. To get this, there is a charge of $150,000 (circa £115,000) per year and you must meet the following criteria:

  • Have either Ecommerce Tracking or Goals set up
  • Have at least 15,000 clicks on Google Search and at least 600 tracked conversions within 30 days
An even better way!

If you don’t have the budget to pay for Google Analytics 360 or don’t meet the criteria, fear not. It is still possible to use a data-driven attribution model and we’ll be revealing all in part 2 of this series next week.

The post Marketing attribution models explained (part 1) appeared first on Vertical Leap.

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According to HubSpot’s State of Inbound 2018 report, generating traffic and leads is the biggest marketing challenge for brands. The same report says 54% of marketers’ top priority is bringing more traffic to their websites. So, despite being one of the oldest digital marketing strategies, search engine optimisation (SEO) appears to be as relevant as ever in 2019.

In this FAQ, we answer some of the most common questions we get asked about SEO:

Is SEO still important?

Search engines have changed a lot over the past ten years and the growth of other inbound channels, such as paid search and social media, make this a perfectly valid question to ask. However, multiple studies from the likes of Sharaholic and Chartbeat last year revealed that search overtook social as the main source of referral traffic for brands for the first time since 2014.

To fully understand the role SEO plays in modern marketing, though, you have to look beyond traffic volumes. Instead, you have to look at the kind of leads search optimisation generates compared to other channels. Paid ads on search engines are generally triggered by high-intent searches from users who are ready to buy now or in the very near future.

These people have typically made up their minds about what they’re going to buy; it’s more about where they’re going to buy from or which specific product/service they’re going to settle on.

With SEO, you’re generally targeting people who are actively looking for purchase advice but haven’t made any conclusive decisions yet. This gives you the opportunity to get in there and influence purchase decisions quite drastically, as long as you can get your content seen in the right moments.

Are SEO and content marketing the same thing?

No. SEO and content marketing are very close relatives but they’re not the same thing. SEO optimises web pages and content to make them as visible as possible at the vital moments. So, you can’t do SEO without content to optimise in the first place but you can do a lousy job of content marketing without SEO.

Content marketing without search optimisation is kind of like a musician writing a bunch of great songs and only playing them in their bedroom. Meanwhile, SEO is the promoter who secures the gigs, air time and interviews so people actually get to hear all of those great songs.

Without SEO, it doesn’t really matter how great your content is because people aren’t going to see it during those moments that influence buying decisions.

Are SEO and link building the same thing?

No. Inbound links are an important signal that search engines like Google look at when deciding how to rank pages and content for specific queries. However, there are hundreds of other factors being considered every time a user hits the search button and it’s important to optimise for them when they’re relevant. (The most relevant ranking factors vary from query to query).

Google’s search algorithm is incredibly advanced now and simply having a bunch of links pointing to your pages is going to do very little by itself. This doesn’t mean having inbound links from high-quality, highly-relevant sites isn’t going to help your search ranking but there’s far more to SEO than “link building”.

Which is better, SEO or PPC?

There’s really no answer to this question as the two play very different roles. As mentioned above, in the ‘Is SEO still important?’ question, search optimisation and paid advertising generate different types of lead.

Generally speaking, SEO generates leads from people early on in the buying process while PPC brings them on board when they’re much closer to buying. On the one hand, PPC leads will often have a higher chance of converting but it’s important to remember the vast majority of consumers go through the early research and consideration process before making a purchase.

The sooner you can build a relationship with these users, the more likely you are to secure the final purchase. And, equally as important, the less likely they are to buy from one of your competitors.

So rather than asking whether SEO or PPC is better for your brand, the more important question is how you can integrate the two strategies to maximise your revenue from every stage of the consumer journey.

Related reading: PPC and SEO – a match made in heaven

How do you integrate SEO and PPC?

Integrating SEO and PPC starts with understanding how these two channels serve your target audiences at different stages of the consumer journey. Organic search normally dominates the early research stages of any purchase decision before paid ads take the lead once users start to show a stronger purchase intent.

So it’s relatively easy to think of SEO as a strategy for generating leads at earlier stages of the buying process and PPC as a channel for getting them closer towards the sale.

The problem is, simply capturing leads doesn’t turn them into paying customers. An integrated SEO and PPC strategy nurtures these leads from one stage of the consumer journey to the next, until the purchase takes place.

This doesn’t happen by magic though. To guide users along the buying process, you need to know what they’re looking for and to determine what kind of message is going to incentivise them to take the next step. This requires a fair amount of data, cross-channel optimisation and a good mix of creative content/ad copy. But the end result is more than worth it because you’ll be maximising the number of SEO (and PPC) leads who go on to make the final purchase.

What’s the difference between on-page and off-page SEO?

Broadly speaking, you can divide search engine optimisation into two categories: on-page SEO and off-page SEO. On-page SEO optimises your pages and content at the code level to make them as accessible to search engines as possible and give them enough information to deliver your content in the most relevant scenarios.

This is where you optimise your page titles, place your keywords, internally link between pages and break your content up into sections that make it easier for readers and search engine to interpret. Other on-page SEO techniques include URL optimisation, alt-text for images and loading time optimisation.

Off-page SEO involves factors that make an impact outside of your website, such as inbound links, citations, third-party reviews and external platforms that can generate search traffic (e.g. Medium, Quora etc).

How much does SEO cost?

SEO is often mistakenly thought of as a cheap marketing strategy but getting results quickly requires a lot of data-driven research and a highly strategic approach to content creation. First, you have to spot the opportunities for growth and then you have to have the means to create and optimise the right kind of content to fill the void.

The opportunities available from one brand to another vary greatly and the kind of content you’re going to need to create (e.g. eBook guides vs video reviews) can be just as varied. So it all comes down to what you’re trying to achieve with SEO, who you’re battling against and how quickly you need to get results.

Got another question about SEO?

If you’ve got a question about SEO that hasn’t been answered in this FAQ, you can get in touch with us on Twitter, fill out the contact form or give us a call us on 02392 830281 to speak to our team directly.

The post SEO FAQs – 7 questions our customers often ask appeared first on Vertical Leap.

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The first thing you probably want to know before you advertise on Facebook is how much it’s all going to cost you. It’s a fair question, but a tricky one to answer. In theory, you can advertise on Facebook with any budget but you’re not going to get particularly great results by spending a few quid every day.

To put things into perspective, let’s look at how much each click is going to cost you.

The average ad click will cost you around £0.79

According to data from HubSpot and nanigans, the average cost per click (CPC) for Facebook advertisers in the UK is $1.04 or roughly £0.79.


A separate study from AdEspresso suggests this is just over the global average of $0.97 and just under the price advertisers in the US are paying per click ($0.10).


CPCs also vary across different industries – it’s notably cheaper to advertise apparel on the network than financial services, for example.


The graphic above from WordStream is based on US data but it gives you a rough idea of benchmarks across industries.

What else affects the price you pay for Facebook advertising?

Average CPCs give you a ballpark figure but we’re not suggesting this is what you should aim for. You want to do better than average and there are numerous other factors that affect CPC such as:

  • Click-through rates: The more people click your ads, the lower your CPCs will become.
  • Ad Relevance Score: Just like Google’s Quality Score, the higher your Facebook Ad Relevance Score, the less you’ll pay for clicks.
  • Facebook ad objectives: The objective you choose when creating a campaigns also affects CPCs.
  • Target audience: Certain audiences are more expensive to target than others.

The better your Facebook advertising campaigns perform, the cheaper they’ll generally become. Highly-clickable, relevant ads are the most important factor in driving down the cost of Facebook advertising. But don’t get too caught up in how much you’re spending when you start to advertise on Facebook; how much profit you’re making from it is far more important.

Did you miss these other bitesize blogs?

Should I care about Bing?
What is AMP?
What is machine learning?

The post Bitesize blog: How much does it cost to advertise on Facebook? appeared first on Vertical Leap.

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When talk turns to SEO, Google is the first name that comes to mind. But, it’s not the biggest name in retail search. That crown belongs to Amazon, which overtook Google as the most popular platform for product searches in 2015 with 54% of the share, according to a 2018 report. Yet the topic of optimising Amazon product listings doesn’t come up in many marketing discussions. In this article, we’re going to cover the basics of Amazon search marketing and how to maximise performance on the world’s largest eCommerce platform.

Getting to know Amazon’s A9 algorithm

In the same way Google’s search algorithm connects users with content, Amazon has its own algorithm to bring retailers and consumers together. The good news is that Amazon’s algorithm is far less complex than Google’s and, while optimising for an Amazon product listing is different from the kind of SEO you might be used to, it’s much easier to get your head around.

The fact is Amazon’s algorithm doesn’t need to be as sophisticated as Google’s because people only use it for one thing – finding products.

Google’s algorithm needs to understand user queries to such an extent that it can differentiate product searches from content searches, local searches from location-independent searches, and all kinds of other use cases.

That’s not to say optimising for Amazon is a piece of cake, but it’s relatively straightforward conceptually and easier to explain in the scope of a single article.

Amazon organic listings vs paid ads

Something else Amazon has in common with Google is that there are two types of listings; organic results and paid search results. Paid listings appear at the top of results pages, based on the keywords users type in, and then users can scroll down to see organic results.

As with any kind of SEO strategy, you’re going to get the best results by combining your organic search strategy with paid ads on Amazon. There are two main ad formats that you need to know about.

Sponsored Products

Sponsored Products appear on product result pages in the same format as organic listings do, except they appear at the top of the page with a “Sponsored” label above the headline. These ads can also appear alongside or within other Amazon product listings and even on product pages themselves.

Sponsored Brands

Sponsored Brands (previously called Headline Ads) allow you to promote multiple products sold by your brand. You can add your logo and a branded message to encourage users to take a look at more of your products.

Once again, your advertising options are more basic on Amazon than you might be used to with Google Ads. But, you don’t need as many ad formats or targeting options because it’s all about those product searches. This means you get high purchase intent from targeted consumers right from the start.

Optimising your organic Amazon product listing

When you’re optimising for search engines like Google and Bing, you’ll generally divide tasks into on-page tasks and off-page tasks. The same thing applies to Amazon SEO so we’ll cover these two topics separately in this section.

Amazon on-page SEO

On-page Amazon SEO focuses on your product listings. There are five key areas you need to optimise:

  1. Product listing title
  2. Bullet points
  3. Product description
  4. Back-end keywords
  5. Product images

Let’s run through each of these elements in more detail to give you a blueprint to follow:

1. Optimising Amazon product listing titles

Much like page titles are a fundamental ranking factor for search engines, the titles of your product listings play the same kind of role within Amazon. These titles give Amazon’s algorithm and users vital information about your products.

Here are some optimisation tips:

  • Include your primary keywords
  • Include your brand name in the title
  • Include product variations (sizes, colours, models)
  • Include defining features (e.g. 4K vs 8K TVs, men’s vs women’s clothing etc)

Keep an eye on title lengths and make sure you optimise for mobile, as this is where a lot of browsing takes place on Amazon. Ideally, you want your titles to be readable and compelling but you also need to make sure all the relevant information is included.

Keep it relevant, avoid keyword stuffing at all costs and remove any unnecessary wording that’s taking up space without adding value.

2. Bullet points

Bullet points are the most important descriptive text on your product listings. This is where you communicate the key benefits and standout features of your products. Bullet points are much easier to read than solid text. This is the part of your listing that people are going to quickly scan and decide whether they want to know more about your product.

Make these count.

3. Product description

By default, Amazon product descriptions are HTML blocks of text, so it’s difficult to make anything compelling out of these. All you can really do with standard product descriptions is include any additional information about your products users might want to know, even if it’s not going to clinch the deal.

If you’re eligible, it’s definitely worth signing up to Amazon Brand Registry, which allows you to create visually engaging product descriptions with images and styled text. These are a major upgrade over standard product descriptions, turning your listing into something more like a product landing page.

4. Back-end keywords

Back-end keywords are search terms you define for your listings to help Amazon understand more about what your products are. These are kind of like meta tags that tell Google what your web pages are about.

You’ve got limited space to work with though, so you’ll want to define these as long-tail keywords that include multiple search terms. For example, if your product is a pair of Nike women’s running shoes, put “Nike women’s running shoes” as a single keyword rather than typing out “Nike”, “shoes”, “women’s shoes” “running shoes” and all the other variations you can think of.

In this case, “Nike women’s running shoes” has you covered.

5. Product images

Images are crucial to any Amazon product listing. First of all, make sure you follow the company’s guidelines for the primary images of your products (the ones that actually show up in search results).

These guidelines vary, depending on the specific type of product:

  • The image must be the cover art or a professional photograph of the product being sold. Drawings or illustrations of the product are not allowed.
  • The image must not contain gratuitous or confusing additional objects.
  • The image must be in focus, professionally lit and photographed or scanned, with realistic colour and smooth edges.
  • Books, music and video/DVD images should be the front cover art, and fill 100% of the image frame. Jewel cases, promotional stickers, and cellophane are not allowed.
  • All other products should fill 85% or more of the image frame.
  • The full product must be in frame.
  • Backgrounds must be pure white (RGB 255 ,255, 255).
  • The image must not contain additional text, graphics or inset images.

Make sure product images are on a white background and large enough for users to zoom in and have a good look at the item. Amazon recommends images of at least 1280 pixels on the longest side but you should really go with a minimum of 2560 pixels for today’s ultra-HD devices.

Amazon off-page SEO

There are four key things that determine how often and how prominently your Amazon product listing appears in results for relevant queries:

  1. Sales volume
  2. Unit session percentage
  3. Product prices
  4. Amazon reviews
1. Sales volume

Amazon wants to sell as many products as possible so it shouldn’t come as a surprise that sales volume is one of the most important off-page ranking factors. While we don’t know the exact workings of Amazon’s A9 algorithm, sales are clearly a key factor. There are different types of sales that appear to have a varying degree of value:

  • First you have on-site, fully priced sales where users on Amazon type in keywords, find your products and make the purchase.
  • There are also inbound traffic sales where visitors click through from another site before making the purchase.
  • Finally, there are discounted product sales and these appear to have lost value in Amazon’s A9 algorithm in recent years.

The most valuable type of sale on Amazon is on-site, fully-priced sales and the more of these you have for any specific product, the more prominently it will appear in search results.

2. Unit session percentage

With Amazon, you don’t get a great deal of analytics reporting built-in, but one important metric you want to keep track of is your unit session percentage. This tells you the number of products that are sold on average per visit to your product page.

This is the closest you’ll get to a conversion rate metric for your Amazon product listing. Needless to say, this is a crucial KPI that provides an overall indication of how well your listing is turning visitors into paying customers.

3. Product prices

Pricing is always a key factor when consumers make any kind of buying choice and Amazon allows people to compare your goods (and prices) with hundreds or thousands of competitors. So it’s important you understand what your rivals are charging for similar products and make sure you’re competitive.

If your products are more expensive, make it clear why people should expect to pay more. If there’s no good reason, you’ve got a problem and Amazon’s algorithm will automatically mark you down if it finds you’re more expensive than the competition.

4. Amazon reviews

One of the most important elements of Amazon as a platform for consumers is its reviews system. This helps people buy with confidence and gives retailers the edge if they’ve got a strong collection of positive reviews for their products.

Naturally, these reviews are going to directly impact your sales and, in turn, your overall performance in Amazon.

Make reviews a core part of your strategy and aim to deliver the best possible service beyond the sale itself. Unless you’re manufacturing your own products, there’s not much you can do about malfunctions or user issues, aside from potentially switching to alternative products.

However, you’re 100% in control of how you deal with customer service after the sale. You’ll often find this is what influences user feedback more than the item itself.

Amazon is the world’s biggest eCommerce platform, handling more product searches on a monthly basis than Google. It’s also a lot easier to optimise for, thanks to its relatively simple algorithm. Make no mistake, this is a crucial platform for today’s retailers and it’s one of the first places consumers go when they’re looking to buy products.

Need help with your Amazon product listings?

If you want to start optimising for Amazon or think you’re not performing as well as you could be on the marketplace, get in touch with our Amazon experts.

The post How to optimise your Amazon product listings appeared first on Vertical Leap.

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SEO is now so fiercely competitive that it’s no longer enough to rely on the standard techniques that everyone has mastered; you need to use data science techniques to unearth hidden opportunities that will give you the edge. This post offers a four-step framework for applying data science to your SEO data and transforming it into actionable marketing insights.

1. Decide on your data sources

Data insights will only ever be as good as your data sources. Where should you look?

Google Analytics and other descriptive analytics tools like Google Search Console, SemRush, Ahrefs, heatmaps and technical audit tools are strong contenders. However, as SEO gets more complex and integrates with other areas of digital marketing such as CRO, content marketing, CX management and ultimately sales, relying on one (or a few) of these solutions is no longer enough.

So how many data sources are necessary to get better SEO insights? The answer will depend on your current setup and post-adoption goals. Consider the areas where your visibility is limited and which data sources contain the answers you need. The next step will be to build a good harvesting engine/pipeline for those sources and to prepare your data for analysis.

2. Use data science to align SEO with other marketing initiatives

Your SEO gets stronger when backed by other marketing initiatives. A single team cannot optimise for all the 50+ search ranking factors without close collaboration with other specialists such as developers, UX designers, sales and customer support teams. Data science helps you figure out a universal set of SEO best practices every team can apply and adhere to.

To better understand what actions matter the most for your business, consider tracking the ever-changing relationships between the dependable and independent variables.

A variable is an event, a sales offer, a campaign or another activity that your company can measure. Data science allows you to pinpoint the relationships between different campaigns (or individual actions) executed and attribute their results to some KPIs (e.g. higher conversion rates).

To get a better understanding of how your SEO impacts other channels, consider capturing and analysing the following data:

  • Conversions and assisted conversions. The latter will help you identify the channels that don’t directly generate the conversions but play a part in the process. For instance, a customer discovered your website via organic search, browsed the products and later typed in the URL directly to make a purchase, or converted from a remarketing FB ad.
  • Top conversion paths. This data will give you more insights into how users interact with your website and other channels before becoming a lead or placing an order.

By gaining a deeper understanding of your customers’ journeys, you can create stronger alignment between all the marketing activities you deploy and attribute the results to individual campaigns with ease.

3. Focus on stories, not numbers

Apart from picking the right data sources/tools, you should also pay attention to the right metrics. Rapid growth in search traffic from Canada may seem like an SEO win, but is that traffic of any value for a business operating solely in the UK? The answer is clear.

Focus on tracking the metrics directly tied to specific KPIs – such as those reflecting conversions, repeat business, higher customer engagement etc. Make sure that you keep a strong focus on quantifiable, actionable metrics, not the vanity ones.    

In addition, it’s important to look beyond the SEO campaign numbers and dwell more on what drives those results. Insights are not just good data summaries. They are stories, explaining certain behaviours your customers are exhibiting and their correlation with your marketing campaigns.  

SemRush suggests focusing on the following metrics to create effective measurements:

4. Use data science techniques to visualise

Numbers stashed in spreadsheets can be hard to stomach for decision-makers. And by looking at your data hierarchically, you can miss an important story hidden between the lines.

Data visualisations can help you:

  • Accelerate knowledge discovery
  • Compare and contrast
  • Spot common trends and patterns
  • Digest large amounts of data at scale
  • Reveal questions that would otherwise be missed

Here’s a real-life example from our team. We leveraged data science during an SEO technical audit and received a lot of insights about the client’s website health and performance. That data told us all about the page authority, number of inbound/outbound links per page, rankings and a multitude of other factors. However, it didn’t provide a clear answer as to why some pages performed better in search results, while others lagged behind.

By visualising the website’s internal link structure and estimating the overall domain authority of each page on a 1-to-10 scale similar to Google, we could immediately see the areas for improvement and take proactive action.


On-page SEO optimisation is just one example of how marketers can combine visualisations with data science to gain better results. Visualisations help you make your SEO data even more actionable.

Ultimately, the goal of data science is to eliminate most of the guesswork from your SEO. Instead of presuming what will work and how a certain action impacts your goals, you switch to knowing what’s bringing you the results you need and how you can quantify your successes.  

Interested in using data science?

If you’d like to start applying data science to your marketing but aren’t sure where to start, give us a call on 02392 830281 or send us your details and we’ll call you.

The post How to apply data science to your SEO data appeared first on Vertical Leap.

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The Accelerated Mobile Pages (AMP) project is an open-source library designed to make mobile pages faster. With the majority of web sessions now taking place on mobile, and the number of mobile-only markets increasing, loading times have become a major UX barrier and conversion killer.

AMP aims to solve this problem by providing a relatively simple framework that makes it easier to create fast, engaging experiences on mobile.

The AMP Project: English Introduction to AMP - YouTube

Project Manager Eric Lindley provides a “high-level” explanation What problems does AMP actually solve?


The framework makes mobile web pages faster and helps brands monetise their pages with non-intrusive ads designed for the mobile experience. There are three key speed killers that it solves:

  • Server requests: Cuts the number of server requests – the biggest cause of slow loading times.
  • Bloated code: Provides its own stripped-down versions of HTML and JavaScript to stop bloated code from clogging up the browser.
  • AMPHTML ads: A faster, lighter and more secure alternative to traditional HTML ads that don’t slow down pages or get in the way of the user experience.

By cutting down on the number of resources your pages need to load, this means less time is spent between your website’s server and people’s web browsers trying to sort everything out.

AMP results showing in Google Search display more prominently than regular results

In most cases, your AMP pages are served by an AMP cache as well, which loads your content almost instantly.

Crucially, your content loads before any ads appear on the page so people can engage with it right away. If you don’t have ads, your text content still loads first while the images progressively load as users scroll down.

Related article: 9 reasons your website doesn’t work on mobile

Need advice?

If you have any questions about AMP, our specialists will be more than happy to help. Just give us a call on 02392 830281.

The post Bitesize blog: What is AMP? appeared first on Vertical Leap.

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