Ideation: How Content Intelligence Powers Product Development
According to a global McKinsey survey, 84% of executives agree on the importance of innovation for companies’ competitiveness. But, only insufficient numbers of high-value ideas enter new product development pipelines creating huge barriers to achieving a sustainable differentiation. Since traditional market research methods – such as focus groups and surveys – don’t deliver adequate solutions, companies look elsewhere.
Benefits of Content Intelligence for Product Developers
Content Science CEO Colleen Jones defines Content Intelligence (CI) as ‘systems and software that transform content data and business data into actionable insights for content strategy and tactics with impact‘. One essential pillar of CI is collecting and analysing publicly available data from various sources such as websites, feedback and review sites and of course social media – comparable to social listening. Product developers and marketers often wonder if such data is worth it when it comes to developing new products or services and the answer is a resounding yes.
Here are some ways as to how CI data is adding value within the process of developing new products or services:
- Gather competitive intelligence: Monitoring online communication enable you to keep track of your competitors and their entire communication – and your industry at large – to incorporate actionable insights into your strategy formulation process;
- Access undiluted customer views: Forums and social media platforms, in particular, provide for a fertile ground to collect honest customer or prospect feedback. Unlike traditional research methods, CI technology allows users to work with vast amounts of data – it also enables product developers to systematically include media sources within their workflows;
- Leverage powerful analytics: Sentiment analysis of, for example, user-generated content (UGC) provide organisations with facts on how target groups’ tonality – read: opinion – is on a certain topic, idea or product. Another example would be what’s referred to as ‘author analysis’ which delivers insights into authors’ demographics such as gender, age, geolocation, social influence and more;
- Market new products or services: Data collected and analysed with CI technology enable product developers – but also marketers and communication pros – to tailor their strategies to the needs of the right audience, with the right content, using the right channels all with a view to maximise engagement and ROI;
- Benefit from data visualisation: The process of insight generation is particularly helped by the different visualisation formats available such as graphs, word and topic clouds, diagrams and many more.
Best Practices of CI-Driven Data Collection and Analysis
Here are some proven best practices to keep in mind when working with CI:
- Define your goals: Specify your information requirements – These will guide you through all steps of the new product development process, from data collection through to analysis;
- Familiarise yourself with CI technology: Make sure to understand how the CI tool works before conducting the analysis. For example, catch up on how the query regulation works in relation to data collection and fully understand the definition and composition of the metrics and analytics the tool comes with;
- Consider the context: Make sure to conduct some background research on the topic you are looking to analyse (including popular keywords and hashtags);
- Don’t rely on just one single data analysis: Always complete different analyses and compare results before making strategic decisions. Such data comparisons translate into higher reliability levels and reduce the risk of failure.
Content Intelligence in Practice: Generating Ideas for Lufthansa’s Customer Service
Customer service is an important factor in fuelling business growth. Using the Ubermetrics tool, we analysed customer reactions to the services delivered by Lufthansa. We employed a simple query based on the terms ‘Lufthansa‘ and ‘customer service‘. We used operators such as NEAR/5 to return only mentions whose distance between Lufthansa and customer service is not more than five characters limiting the number of irrelevant mentions. We gathered social media reactions from the company’s customers in a three-week period in October 2019 with the following results:
Sentiment Analysis: Identifying the Tonality of Customer Conversations
The sentiment analysis feature of Ubermetrics provides insights into customers’ attitudes and perceptions towards any topic, organisation or product. Below we can see that customer feedback for Lufthansa is predominantly positive:
Here is an example of a customer that is satisfied with Lufthansa’s services and shows his appreciation for the airline:
Henning: If it’s not a Boeing, are you going?
Lufthansa airlines has nice aircraft, lounges, service. Can get personal assistant to drive you from the aircraft to the airport when deplaning, custom meals at restaurant, top-shelf drinks #chicagoseminars
— HurdyGurdyTravelPodcast (@HGTravelPodcast) October 19, 2019
Such positive feedback can be helpful for product developers as it indicates that the service in question is generating customer satisfaction.
Many organisations are wary of criticism, especially when seemingly negative comments are published online. In the below example, a Lufthansa customer is sharing a negative experience she had with the company on Facebook. With this feedback, Lufthansa can detect inferior service quality with a view to optimise said processes but also to provide an immediate solution:
Topical Analyses: Which Topics Matter to Lufthansa Customers
Ubermetrics’ topical analysis tool helps organisations to identify the most used terms around any brand, product or topic which can then be integrated into the respective product development process.
Based on the data collected, the visual below shows that terms such as flight, baggage, contact and compensation pop up in customer conversations, suggesting potential customer service-related issues. Analysing conversations that include these terms will provide the company with an overview of issues from a client perspective.
Diving deeper into the conversations around the term ‘baggage’, we can see that Lufthansa has been receiving complaints about their ‘baggage’ service. Those two customers do not only complain about losing their baggage, but they also mention missing refunds. By monitoring such mentions, Lufthansa can identify such problems, investigate their nature and try to find solutions to ensure customer satisfaction.
@lufthansa i have several emails for feedback id 33436773 reagarding the compensation for baggage delay but haven’t recd any response, i never expected lufthansa to be irresponsible towards customer to compensate them very poor from lufthansa.
— Franklin Thomas (@Frankli38954687) October 9, 2019
@lufthansa anothet appalling service from Lufthansa twice in the last 3 months my baggage wass daelayed and now I have missed a flightsue to a late arrival of the plane in Krakow, this despite being told we would be OK whilst on plane from Krakow, shocking!!!
— Neil Morgan (@nmorgan1123) October 17, 2019
The examples we list here reflect on a very high-level view of the opportunities that come with employing CI technology within product development. Users can use many different Ubermetrics features such as source and media segments analysis, geolocation and virality signals. If you want to learn more about how Ubermetrics can support you, get in touch with us today!
This post was written by Thanh Nguyen Dao, a Master graduate majoring in Media Development at Darmstadt University of Applied Sciences, with a professional background in Marketing.
Thanh’s interest in Social Media Monitoring has been sparked as she joined the project Social Media Monitoring at a pharmaceutical corporate in Germany.
The Ubermetrics team thanks Thanh for her interesting post.