- Augmented Analytics
- Big Data Analytics
- Business Analytics
- Data Governance & Data Fabric Architecture
- Data-Driven Strategy & Transformation
- Performance Management & Improvement
- Qui sommes nous
- Insights Room
- Webroom & Events
The ubiquity of social media in our lives provides what is essentially every marketing team's dream: a treasure trove of personal information you can draw upon in order to glean behaviours, interests, needs, and preferences.
Nov 09, 2017
Engage, Discover, Decide – The three buzzwords of consumer interaction
Today, the main drivers for new service adoption and customer engagement are speed, convenience, and interaction with retailers. Most companies have currently access to an incredible amount of consumer data collected from a wide range of sources, from online browsing, day-to-day interaction with customer service and brand social media channels to actual purchases both in online or physical stores. Unfortunately, companies often lack the resources to leverage this huge amount of information in order to spot behavioural patterns and turn them into actionable insights.
With the rise of the global economy and the contribution of the internet, more and more companies are vying for the attention of your customers. This is why it is vital, now more than ever, to be able to understand how to capture and, more importantly, retain your consumer base interest and business. Fortunately, the ubiquity of social media in our lives provides what is essentially every marketing team's dream: a treasure trove of personal information you can draw upon in order to glean behaviours, interests, needs, and preferences.
With Facebook's announcement of reaching the milestone of over 2 billion monthly users (source: CNN) for Q3 of 2017, averaging hundreds of thousands of posts and comments a minute, manually scanning your consumer base posts for clues and identifying relevant population clusters would be a superhuman task. This is where cognitive computing comes in.
Cognitive APIs help researchers analyse the content of an unstructured text (like documents, emails, posts or tweets) and contextualise it, based on advanced semantic rules. It is also possible to construe the tone of the writing and create a psychological profile of the poster, based on their writing style.
Let's look at a few possible applications.
Brand reputation – How does the public feel about your company?
Applying sentiment analysis to brand reputation has been a sort of pioneer in using text mining to understand customer interactions. What looks like a simple problem – scraping public posts containing the name of your company and products, and searching for positive or negative wording – can prove to be very challenging and nuanced.
First of all, it is important to identify the aspects to focus on: public opinion of your company may be very positive, but your newest product might still be underperforming. How does the impression your customers have of your company's core beliefs influence what they think about the company's products? How did the most recent announcement from your CEO impact which search terms are connected to your brand? How does world news affect your sales? Apparently unrelated topics all concur with your brand image.
Secondly, it is important to make sure the cognitive system you are using can contextualise and interpret data. The difference in wording between a genuinely happy customer's tweet and a frustrated one's could be as subtle as the addition of an emoji. For example, "The "awesome" new iPhone X face recognition does not work in strong lighting. Just brilliant! :/" and "The new iPhone's facial recognition is awesome! Brilliant product, Apple!!!" convey very different meaning, which is clear to a human analyst but might trick a simple automated search for positive or negative keywords. An advanced sentiment analysis system is going to be able to infer the actual tone of a post and help you interpret the true meaning of your customers' posts.
Meet your customers – Who is your audience?
Getting generic personal data such as gender, age or income can be relatively easy: all you need is a customer profile on your e-commerce page or a filled-out application to a customer fidelity program, but what about their tastes? By studying the way your customers engage with you and what they say about themselves on social media, you can understand their preferences and inclinations. With cognitive APIs, you can match the writing style of a user to a set of personality traits that can help you identify the main qualities of your audience and react accordingly.
Are your customers generally daring or cautious? Extroverted or introverted? Open or closed to change? Do they value stability over the achievement of success or is it the other way around?
By answering these questions, you will be able to tailor your social media presence and your marketing campaigns to enhance your appeal to the population groups that interact with your brand, thus improving engagement and customer retention.
Similarly, you could work backwards, by deciding which population segments you want to interest in your brand and products, and then tailoring announcements and posts to them.
A customer profile created with Watson Personality Insight
Other people also bought… – Anticipating trends and creating new needs
After attracting new customers, the most important topic is their retention. To ensure future interactions with your customer base, you need to anticipate what their needs are going to be and propose products and services that align with that. In the internet age trends grow and fade at lightning speed and being able to mine your current and prospective base with an automated tool can give you a great advantage when it comes to predicting them.
To do so, you can use your existing data on previous transactions and associate it with the population clusters provided by a cognitive API. This way, you will be able to tailor offers and suggestions to new customers, not only based on your general population's purchases but by applying a laser focus to the characteristics that make each consumer group special and unique. Hence, your customers will be able to find the products and services that are right for them as individuals or as companies, and you will be able to anticipate their needs by offering new solutions even before they search for them.
Are you ready for a cognitive approach to customer interaction?
Like all advancements in technology, no matter how powerful your IT systems are, or how much data you can obtain from your customers, what is really going to make a difference is your company's attitude towards these new tools. So, is your company ready to start actually using your data to obtain new insights?
Ask yourself a few simple questions:
- Is creating an engaging tailor-made experience for your customers a priority for you?
- What are your company's short-, middle- and long-term plans to achieve this?
- Do you really know how much of your structured and unstructured data you are using across your business?
- Are your analysts open to new technology and new technical developments?
- What are the business cases you would tackle first?
- What kind of results would you expect from this system in the short, middle and long-term?
Once you have an answer to these questions, you will be able to start envisioning a cognitive future for your company!