To understand digital analytics, there are some essential headlines that help us make sense of what we are dealing with leading up to 2020. There are over 5 billion unique mobile users in the world, almost 4.5 billion internet users, 3.5 billion social media users and 3.26 billion people using social media on mobile devices. All these numbers are still growing year on year as areas that previously couldn’t be connected, such as African nations, are now some of the fastest growing communities.
Arguably the biggest market is in the US where 77% of Americans are online every day. Each of them will consume content differently and have varying demands. Digital marketing is a crucial component of 2019 strategies and beyond but only if it is accompanied by effective digital analytics.
What are digital analytics?
Traditionally, when talking about digital analytics, the platforms that spring to mind are those specialising in website data such as Google Analytics or the Adobe marketing suite. Companies were aware that they needed to track their website performance and optimise it. Digital marketing teams had some tools available to report and analyse their web analytics.
However, as the digital world has grown quite exponentially over the last decade, so has the number of channels available to marketers and consumers. Beyond this, there is a vast amount of data stored up in Big Data platforms offering a wealth of valuable business information.
Digital analytics is more than just the web analytics now. It incorporates all the connected online channels that a consumer base uses to analyse their behaviour and maximise revenue opportunities. It gives marketing a data driven foundation to provide a strategy for optimising digital activities. This article looks at some of the key channels for digital analytics, the type of data you get from those and how that data can assist in making business decisions.
Digital Analytics Channels
The are several data gathering channels that feed into a digital analytics strategy for efficient tracking customer behaviour. Recently we have seen the rise and growth of new ideas in artificial intelligence (AI), chatbots and machine learning (ML) to give digital marketing teams a lot more to think about. It is a very exciting time to be a marketer with an amazing mix of channels to blend together and increase return on investment (ROI).
When looking at digital analytics, businesses will need to align with the overall strategic goals. Each channel most likely has its own key performance indicators e.g. getting more traffic to your website or increasing the number of likes on social media videos. Every business will be looking to increase income, but a strategy will generally be led by brand awareness, lead generation, customer retention or achieving more direct sales.
The channels you choose to use for digital marketing will largely depend on your business and the target audience. Not every channel will be applicable to your objectives. For example, generating new leads tends to focus on search engine optimisation (SEO), mobile marketing and content marketing whereas to improve brand awareness, you might focus on social media and email marketing.
Here are some of the most popular and come digital channels and the sort of metrics you may look to measure with each.
All digital marketing professionals will have completed some form of web analytics. Your website is designed (or at least it should be) to have top quality, optimised content for anybody who visits. It is the place where you can really promote your brand as you see fit and create an engagement strategy that you, and only you, own. There are a huge number of metrics that companies use to track the performance of their website. Listed below are a few of the key ones.
- Number of visitors. A visitor is somebody who visits your site and there won’t be any activity without them. This gives a direct indicator as to whether people are able to find you.
- Source/medium. This provides the number of visitors who reach your site via different channels such as social media, email, other sites and so on. It shows where your digital marketing has been the most effective for generating leads.
- Device. It is important to track visits against devices used i.e. mobile, desktop or tablet. If most users visit via a specific channel, it is important to focus marketing efforts in that direction and optimise performance. Digital analytics platforms can show the speed of different devices and how efficient they are at handling your web content.
- Bounce rate. Whilst you might get a lot of visitors, the bounce rate gives a percentage of those that never interacted with the page they landed. It is a good measure of quality content and a low rate shows that your site contains information that the user would expect.
- Time on page. A metric like this tells you how much visitors engage with your content or whether it needs optimising
- Conversion rate. Do visitors to your website complete a call to action such as a purchase or quote submission
There are lots of social media channels and they don’t seem to be going anywhere fast. Some of the most popular for digital marketing efforts are Facebook, YouTube, LinkedIn, Instagram, Twitter, Pinterest, Tumblr and Vine. Each of those has their own benefits which are worth looking into. The fantastic part of social media is that it has such an enormous reach. As opposed to users trying to find your website via Google or another search engine, social sites give brands the ability to push content to the masses.
Where companies fail in social media marketing, it is usually down to poorly planned content. A lot of businesses might prioritise volume over quality. Whilst this might generate leads and views, the chances are it won’t create true customer engagement. According to Global Ambassador, 71% of consumers having a positive social experience with a brand are likely to recommend them to others. These “free” referrals are the dream of digital marketing teams.
There are several metrics for measuring social medias success to ensure you get the best possible content out to potential customers.
- Engagement rate. This shows the total number of comments, clicks or likes against your social media content usually as a proportion of the number of views. Straight away, it tells you whether people are taking the desired action from your posts.
- Followers/Subscribers. Every social platform gives viewers the option to follow the brans that posted the content. The number tells you how successful a specific post was at generating potential leads.
- Shares. Another metric that is common on almost all social networks. The number of shares shows how many times a page or post was shared on other social media or via a website or blog.
- Cost/Cost per click. A bit like Google pay-per-click, Facebook and now Instagram offer brands the chance to push paid ads out to their leads. It is important to measure the cost of these versus revenue, so they can be targeted at the right audience
Social media stories have also increased in popularity over the last 12 months via Instagram, SnapChat, Facebook and YouTube platforms. Mark Zuckerberg has publicly stated that he expects stories to overtake regular posting via Facebook and the other platforms they own. Stories feature short snaps about a business, normally in the form of video content. As opposed to scheduled posts, businesses can tell a narrative and experiment with the formats that work best. The metrics are largely the same as those already discussed but with this format, there is greater scope to be creative with content.
Voice Search and Natural Language Processing (NLP)
It has been predicted that as much as 50% of searches will be voice-to-voice by 2020. A lot of this comes down to the popularity of devices like Amazon Alexa and Google Home which has revolutionised how we use verbal communication.
For digital marketing and analytics, it creates challenges as the way results display are very different to text. Devices like these use what is known as natural language processing to interpret the commands and return what it believes is the correct result.
The way that people search means that some businesses need to rethink their digital marketing strategy to counteract potential errors and missed opportunities. Beyond searches, businesses now use voice analytics within services to better understand their customers.
- Word error rate. Recognition accuracy of each individual word
- Semantic quality. How closely the voice results match the results a user might type in
- Latency. Time it takes to complete a voice search
- Out-of-vocabulary rate. How many spoken words are not accounted for in voice models
When thinking about digital marketing, it is important to adapt SEO and PPC strategies to the way people will speak as opposed to type. Digital analytics platform can track your campaigns and keywords strategies to show what works and what doesn’t. Many teams are adding voice search specific campaigns that are generating a good return on investment.
Email is still and probably always will be a key digital marketing channel but over the last few years, it was continued to evolve. The days of creating some content and bulk sending it to an entire customer base are long gone as businesses strive to ensure their customers receive quality, relevant information. Digital marketing strategies will have a focus on personalisation or even hyper-personalisation. This goes beyond ensuring we call somebody by their name or vary subject lines and produces dynamic unique content for different customer groups.
Customer segmentation or clustering techniques will be used to identify groups who have matching attributes e.g. age, gender, location, purchasing patterns, occupation, spend. Those segments will receive communications tailored to how they like to receive emails (day of the week, time of the day) and the sort of content they are most likely to relate to.
The most important part of deploying a personalisation strategy like this is analysing that it works. It might take a lot of trial and error when working out the type of communication that some groups respond to and those that don’t.
- Open Rate. This will show you the number of emails that are opened as a percentage of the number sent. It indicates that the subject and/or content was relevant to the receiver.
- Click through rate. Once the email has been opened, the click through rate tells you if the receiver took and action. This is usually a link within the email to go to a website or social media page perhaps
- Bounce rate. The number of emails that were never received as a ratio of those sent. It is a good measure of how well governed your database is
- Unsubscribe rate. If people receiving emails unsubscribe to receiving future content, there is a clear message that the information is not relevant to them and needs optimisation.
Each of the metrics should be measured for every segment that you have set up. Over time, through optimising content, you should start seeing improved open and click through rates as well as lower unsubscribe rates.
In the last few years, chatbots have emerged as the most popular communication channel between a consumer and a business. Some experts have estimated that by 2020, chatbots could control as much as 85% of all customer service.
In short, a chatbot is a program or machine that attempts to answer conversations as a human would. The objective is to help customers with tasks quickly, so they haven’t got to call in, saving cost on staff whilst ensuring a positive customer experience.
If investing in chatbots, digital teams need to ensure they are high quality. Projects in this space tend to fail if not enough thought is put into how they are developed. If Alexa or Google Home never knew the answers, nobody would use them as they don’t serve a purpose. The same applies to a chatbot. If it doesn’t store information that your customers would find useful, there isn’t much point in it being there.
Chatbot metrics that can be used for digital analysis would include:
- Customer satisfaction scores. Is the chatbot successful in ensuring customers are kept happy with the answers it provides
- Completion rates. The number of chats that have an end. This will usually be distinguished when the chatbot uses a term labelled as an end of conversation
- Text analytics. Using the speech to see what customers are asking. They might be referring to issues on the website leading the digital team to make changes.
- Reuse rate. Do people use the chatbot more than once or do they try another channel the next time. This might be more applicable to retail situations rather than customer service where you don’t generally want customers to need to come back
- Miss messages. How many messages the chatbot could not answer to understand how efficient it has been or whether work is needed on the knowledge base.
Having video as part of the digital marketing strategy seems to be a no-brainer. In 2018, 85% of all internet users in the US watched online video content monthly and research by HubSpot has suggested that 54% of consumers want to see more video from brands they support. Social media trends to be the main avenue for posting videos as it is so far reaching but brands are using it within their own material to strong effect.
Some digital marketing professionals have said that Facebook is likely to be a video-only platform within the next five years due to the way consumers absorb the content. There are a number of key metrics for measuring video suggest that will be picked up within digital analytics platforms.
- View count. Naturally you need to make sure people can see the video. View count gives an indicate of the potential reach of any content
- Play rate. Of those who viewed the video, this gives a percentage of how many played the content. It gives a measure of how relevant the content was and if the audience was correct
- Engagement rate. This shows how much of the video users watched as a percentage. It is all well and good having a large reach but if users switch off, the content doesn’t provide the desired value
- Social sharing. How many times was the video shared on social media.
- Click though rate. Did the video lead to viewers taking an action? This is arguably the best measure of success as it shows that the content has/doesn’t have the needed response.
Artificial Intelligence (AI)
AI is a broad subject and there are countless applications. In terms of digital marketing, it can be incredibly powerful when trying to identify potential leads, recommending products or handling customer experiences. For example, an application of AI known as machine learning can analyse all your existing business data to predict which customers are best suited to your next email campaign. Imagine you have a campaign about travelling to Italy. Machine learning tools can analyse millions of data attributes for all your channels in seconds to suggest customers likely to respond.
This sort of intelligence is the basis for recommendation engines like Spotify, Amazon and Netflix. The metrics for the technology are dependent on application or device but they would include some of the below.
- Recommendation success. Did customers act on the recommendations provided to them? Netflix have said that 80% of subscriber viewing choices are from recommendations. If this figure is low, it would suggest the algorithms use need optimisation.
- Conversion rate. If campaigns are targeted based on recommendations, you would expect a significant increase in conversion rate given the audience are always receiving content relevant to them.
- Spend vs Revenue. In utilising AI tools for predictive digital marketing, the amount of spend against income should fall or as a minimum be more efficient.
The mobile app industry is saturated with a huge range of tools and applications for users. This makes it incredibly hard to develop something that people genuinely have a need for on their device and are willing to keep for more than 90 days (the average retention). Many brands are moving towards Progressive Website Apps (PWA) which are internet browser based but give the same experience as if using a downloaded application.
However, if you have spent time and money developing a mobile app, there are several metrics that can as a guide to measure success.
- Mobile downloads. The number of people downloading the app to show whether it is something they feel is needed
- Retention rate. Once people have your app on their mobile, do they keep it and if so, how long to they keep it for
- Sessions. If somebody has downloaded the app, this measures the amount of times they use it over a period.
- User growth rate. Simply, is the user base for the app growing.
- Subscriptions/purchases. If applicable, are people spending money via the app and performing the actions you would expect
- Return on investment (ROI). Apps cost a lot of money to develop so any activity must have a return associated to it.
And across all channels……
There are some metrics that should be tracked across every channel that you use. These would include demographic data such as the age or gender of users as well as their location. If the digital marketing strategy is set to target certain groups, even if engagement rates are high and you are hitting revenue budgets, they still need to be attracting the right brand customer. For example, if your brand is designed for 24-30-year-old females and you get a high engagement rate from 40-45-year-old males, whilst the metric is strong something strange is happening.
The digital analytics platform can only provide the metrics. It is still important to ensure you have a tailored digital marketing strategy with a foundation of the 5Ps of marketing (place, price, promotion, product, people).
You have all your digital marketing channels in place and know exactly what metrics to look at as part of the digital analytics strategy. The next step or working out the best way to achieve a return on investment from the different marketing efforts. Sales leaders want to drive and scale meaningful changes that can pay off tomorrow and in the future. The next article in this digital analytics series will focus on creating a strategy that optimises marketing and generates a return on investment.
This is a series of articles. The next article on an in-depth article how to increase your return on investment using Digital Analytics. The article is available online; How to use Digital Analytics to generate ROI