- Increasing number of channels (web, email, social, mobile) broken down into even smaller sub-channels is making digital mktg complicated
- Digital mktg is not so intimidating once the basics are in place
- Contextualisation, simply put, is next-gen consumer personalisation
- ‘Digital Hugging’ is a simplified version of contextualisation
The age of digital engagement is so far upon us, most marketers can barely remember a time it didn’t exist. And it’s not just for big companies or tech-savvy marketers – businesses of all sizes are increasingly reaping the benefits of well-planned and properly executed digital marketing campaigns, which for the most part are relatively easy to initiate.
What makes it more complicated though, is the increasing number of channels — web, email, social, mobile — used by customers and prospects, that are broken down into even smaller communities and sub-channels (for example , the move from Facebook to smaller and intimate communities like the ones that technologies like WhatsApp, Vine, WeChat, Snapchat and many others). In short, the job of the digital marketers is ever challenging, and sometimes the focus is directed too much towards the channels – which channel is trending now and how to make use of it, without any real objectives behind what we are doing and why – for example the ROI or value these campaigns are providing; does an increase in followers = more success?; does it translate to an increase in revenue?
While Digital Marketing can be complicated, it’s not so intimidating once you have the basics down.
Here are three ‘common’ marketing objectives:
1. Convert leads into buying customers
2. Increase the LTV of your customers
3. Win-back inactive and lost customers
Let’s look at the customer lifecycle and its journey from a lead to a churning customer. The chart above explains the journey visually, and thus are the strategic objectives:
#1 Convert leads to customers
Most of the budget we invest in digital is directed towards acquisition strategies – SEO, PPC, Facebook ads, banners, affiliation, and so on. The true objective is to take the leads we invest so much money in and convert them into buying customers.
We need to measure how much money we spend on each channel against the conversions we have. If we do not do that, then our acquisition strategy is merely a hobby. Assigning dollars amounts to each channel and looking into conversions, is often called attribution Hence what we want to do here is measure increase in conversions against our actions while assigning desirable targets, e.g. 20 per cent of my leads are converted into buyers each month.
# 2 Increase LTV
Given the investment we’ve made in acquiring the customers, every sell we will have from now onwards will yield larger gross margins. It should be noted that the purchase cost doesn’t include the acquisition costs anymore. And hence what we want to do here is to look into the increase of the spent from our existing clients and make sure they are retained. Here you need to look into increase in the average purchase from your clients and increase in their engagement metrics (more visits, increased time on site, review of products, etc).
# 3 Win-back
The third and last objective is trying to pull back the customers who churned or are inactive toward the centre of the customer lifecycle, so that the pool of customers we have will churn in a slower pace — twist it, turn it, customers will always churn. The best you can do is to delay their churn.
I will not go into the tactics used, but looking at the strategy, you want to measure win-back ratios (churning customers – churning customers who purchased again) and work against improving this number.
It doesn’t really matter what type of business and industry you’re working in. The job of the digital marketer is sales, and by sticking to these objectives and measuring against them we’re ensuring our efforts are directed towards the bottom line. You can now look at different channels and campaigns, but make sure that everything you do is attributed to one of these goals.
Digital Engagement in a nutshell
Once you’ve defined your goals, you’re going to need a strategy; and for that, you need to think like your customer. There are four different questions that, if understood and answered correctly, will provide your customers with the ultimate brand experience (or customer journey):
1. Who is the customer – and where are they along your customer life cycle?
2. What content best fits the customer based on past behaviour, purchasing patterns and browsing history?
3. When should the customer be reached (this depends on their stage in the life cycle)?
4. How/ where to reach the customer – look at their preferred method of communication
Contextualisation, put simply, is next-gen consumer personalisation. “Advance To Next-Generation Personalization,” a recent Forrester report, defined contextualisation as a tailored experience that meets the individual user’s needs by combining historical, behavioural, and profile data with real-time situational feedback. Essentially, it’s the next step in customer experience targeting – going a step beyond normal personalisation by adding customer data (who the customer is), Historical data (what the customer did in the past) and situational data (what the customer is doing now).
Which brings me to ‘Digital Hugging’, a simplified version of contextualisation. Digital hugging is essentially the ability to surround the customer or prospect with love and affection across the main digital channels we have while providing him with an experience relevant in the context and time most relevant.
For a portion of that much wanted love and affection from your current or future customers, follow the recipe with the cooking instructions:
1 recommendations engine
1 email system
1 plug-in from your web analytics to your database
A lot of customers
Website with traffic
1 plug-in for the purchase history of your clients
#1. Take the scripts of the recommendation engine and implement on your website.
#2. Allow the machine learning algorithm 2-4 weeks to learn your users’ behaviour.
#3. While on medium heat, ensure the plug in from your web analytics/recommendation engine is connected to your customer ID on your database. It means that you will have the possibility to identify the web behaviour and email behaviour of your clients and prospects.
#4. Close the lead, and let it work its magic for 2-3 weeks.
#5. Take the plug in for the historical data, and link historical purchase data to the customer ID (be it an email address, first name/last name, customer #).
#6. Now your database contains: email behaviour, web behaviour, and also historical transactions (hint: you can add also social data if you use companies like Gigya for instance).
#7. While the gourmet dish is cooking, implement the recommendation engine widgets on your staging website, test them against other content you think can do better until the flavour of the algorithm is perfect. Recommended widgets: related (related content to the one your users are browsing on the product level – complements a set of products to the product they view. E.G – related to camera are: memory, cleaning instruments, and a bag), personal (locate it on your main page, so the user receive content relevant to him), also bought (people who bought this product will also buy that product), and cart (allow the user to add easily recommended products to the cart, and by this increasing the cart value).
#8. Let’s rock n’ roll. When everything works, move the widgets to your working website.
#9. Engage customers based on their situation: dropped carts? Send an email with recommended products to the one the user wanted to purchase based on his/hers purchase and web behaviour. No response to email? Retarget customers with dynamic content recommendation (attention: not static banners, but recommended products based on historical purchase data and browsing history). Customers not visiting the website? Follow them with email recommendations and or retargeting and try to bring them back to the products they like.
#10. Identify more situations based on channels, locations and behavior and use data, channels and content to engage your customers.
#11. Measure your customer engagement and CLTV. You’re looking for an increase in the metrics.
Hope it helps to simplify the concept digital engagement, digital marketing and contextualisation. It sounds complicated but it’s a lot easier in practice, especially if you know your business and have basic understanding of your customers. And don’t forgot you’re not going at it alone – there are lots of different technologies are available in the market and becoming accessible to SMB’s to assist or help you get started. In the meantime, check out TripAdvisor, a great example of a company who gets (and has properly implemented) contextualisation, and is using it to strengthen their business concept and grow their customer base.