22. April 2021 By Heike Heger
Four important aspects to help you map the customer journey perfectly: #2 Personalisation
Anyone involved in content marketing should also be concerned with the subject of personalisation. A simple example illustrates why personalisation is so incredibly important, especially online: when I’m on my way into town, I don’t necessarily expect every shop along the high street to greet me with, ‘Hi, Ms Heger’. I know where I want to go and prefer to shop in 1a locations – that is, in the middle of town. 1b or even 2a locations have a hard time catching my attention – unless they’re relevant to me that day and are worth the trip. And that brings us to the point: high relevance is a decisive factor in customer contact. That’s why content is only worthwhile if it interacts with the customer in the right way.
Make the ‘1a spot’ in online shopping yours with personalisation
Of course, personalisation in 2021 doesn’t just mean the basic, ‘Hi, Ms Heger’ and addressing customers by name with any selection of products. Personalisation today refers to a plethora of finely tuned information and triggers that correspond to the individual product preferences and behaviours of the potential buyers, which are coordinated and are published on the corresponding channels to create a targeted customer experience.
And what makes optimised personalisation measures stand out is that recommendations are generated on the basis of behavioural patterns and user preferences of each individual customer – meaning they can proactively initiate the urge to purchase in the ideal scenario. This is done by using artificial intelligence to automatically identify customer interests, derive patterns from them and use machine learning to predict which products the customer is likely to purchase. This kind of intelligent knowledge of customer needs gives suppliers the desired edge over competitors that employ traditional marketing measures.
Powerful digital experience platforms (DXP) offer cloud-based personalisation services to deliver an AI-based customer experience to every customer.
What should you keep in mind when it comes to personalisation? Here are a few tips:
Where are you going?
First and foremost, think about what your goals are. Dive into the details and find out what your company really means by personalisation and what you ultimately want to achieve with your customers. This will allow you to formulate the requirements for the subject as well as for a DXP with greater precision.
What are your specific requirements?
Illustrate and specify what you are looking for with examples. You can use personas or user stories to better illustrate your personalisation requirements. Examples from other companies are also helpful here.
How do you want to proceed?
One thing I can’t stress enough is to start small – a good way to do this is within the framework of an MVP. First of all, test how the personalisation measures work and how they are received in a limited environment. It’s only worth rolling out on a large scale once you’ve done that.
Personalisation – be better than average
Most media sites use current and trending content, usually based on simple statistics, to show the most popular topics at a given time. But of course this is nothing more than scattergun marketing – the customer is 20-year-old student, so let’s show them an advert for a pair of trainers. More advanced recommendation engines use predictive analytics to deliver more relevant content that is likely to trend in the coming hours. Staying with our example, the customer is a 20-year-old student who likes to wear black and white and has recently ordered a stylish, black-and-white outfit, so now we offer them matching shoes and accessories.
Semantically linked recommendations require high-quality meta-information and content linking. One example is linking the state of someone’s health to a particular food choice. For example, a customer has a gluten allergy. As a result, they only receive adverts for products they can actually eat, plus some exciting recipes.
That means relevant information (such as articles viewed, social media behaviour, areas of interest) can be used to identify patterns of behaviour that lead to a significantly higher likelihood of conversions. Content recommendations can deliver more targeted content based on similar behaviour and content consumption of other users.
Websites that are commercially run and have clear key performance indicators (KPIs) can link recommended content or products to KPIs that are important for net profit. KPI-driven recommendations are powerful because they are based on self-learning algorithms that link user behaviour to predefined KPIs.
This means that we’re dealing with a number of variables that can be set perfectly by a DXP.
Variable 1: Conversion scenarios
- Reading an article or watching a video
- Sharing an article on social media
- Purchasing a product
- Registering for a free trial or demo
Variable 2: Recommended products
- Products that are in stock (and need to be sold quickly)
- High-margin products
Variable 3: How the recommendations are made
- Trend recommendations: Today’s top items or best-selling products.
- Semantically linked recommendations: Related content within the same category, tags, topics, companies, products or people.
- Behavioural recommendations: People who bought a product also bought a similar product you might like.
- KPI-based recommendations: A product that matches a defined KPI and achieves a conversion based on user behaviour.
The fine art of personalised customer contact offers a plethora of different possibilities. No company worth its salt can ignore them. The more personalised the contact, the less wastage your marketing campaign will have and the better it will succeed in turning interested people into users and then into long-term customers. The general rule here is think about what you’re saying rather how big the font is. And this is where using a DXP helps enormously, as it is ultimately acts as the ‘keyboard’ for all of these communication options.
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