Issue 5 - Building blended content and data products
There are just 51 days left in 2023, and already people are looking towards plans for 2024 and beyond. During our conversations with clients and industry colleagues, one big question keeps recurring - how can companies better blend their content and data assets to maximise their value? This isn't as simple a question as it may sound, for many of our clients this requires a complete audit of their assets and architecture, as well as deep audience research and discovery to support ideas for new products and user experiences.
In this issue, we'll explore the key ways publishers can get started to tackle this fundamental opportunity, including an interview with Will Bailey, our Head of Partnerships and a guide to breaking down siloes for technology leaders.
Interview: Will Bailey, Head of Partnerships
What do we even mean by bringing content and data together?
First, it's helpful to define what we mean by 'content' and 'data' and why they're different - at least in this context. When we talk about content, we mean long-form analysis, insights, commentary, written reports, blog posts, research papers, books, monographs - anything written that's in-depth and non-numerical.
Data might be compiled datasets, health data, market sizing, sales data, economic data, but it could also include exhaust data that companies have not previously monetized. Part of what we do with companies is provide a full review of all the data they own and generate and look for ways they could use it better for commercial advantage.
It's fairly standard for companies to sell a large, static dataset and then produce reports alongside it. We argue there's a big opportunity to join these things up and enrich them to create a more unified, useful user experience, as well as opening up new opportunities for better sales models and new product creation. This might include value-added services like visualisations and analytics that deepen the story the data tells for your customers.
What are the key benefits of blending content and data assets for publishing and information companies?
From the customer side, the benefit is that they get the insights they need, faster, with added context and personalised experiences.
For companies, you will deepen the strength of your brand by engaging with your customers in more places across the value chain, allowing for more sophisticated sales models and creating pathways to increase retained revenues. It also sets you up with the flexibility required for responsive new products to be launched at pace to support a changing marketplace.
What are some common challenges and pitfalls that organizations may encounter when trying to blend content and data assets, and how can these challenges be mitigated?
Breaking siloes and turning the different stores into something that's interoperable and speaks to each other is hard - often the assets haven't been tagged in a way that makes this easy or quick. You need to start right back at the beginning of the way your content and data are processed and stored, before you think about front-end delivery.
Other issues can be around having the right commercial team set-up to take advantage of new models and products. Sales teams are often very good at delivering revenue via tried and tested pathways but need new strategies to really realise the commercial benefits released by new product offerings, or sell under new models.
Which companies do you see doing this well?
Obviously, I'm a little biased, but EIU are doing a great job in this area. They've got fantastically well-respected data and insights to share, and they've brought them together really successfully with their Viewpoint platform. Enhesa Product (formerly known as Chemical Watch) have done this with lots of different content types such as transcripts and data from events, pulling them into a cohesive product offer which provides crucial compliance and regulatory information to companies working with chemicals.
Outside of our client base, Wood Mackenzie, who provide market intelligence in the energy sector are also doing a great job of this. Finally, The FT and McKinsey are also great examples of companies that enrich their journalism with excellent data and visualisations.
Is there a role of Gen AI and machine learning here?
There's definitely a place for AI to make things like content categorization faster; rapidly tagging and organising both numerical data and text so it's in a workable state. For example, the intelligent automated tagging we created for Enhesa enabled the creation of common metadata so that all their assets could fit into the same user experience.
Gen AI can also be used for summarization of data, for example showing it a graph and asking it to provide context or tell a story can open up ideas for how you can start creating content links.
Can you share insights into the ways in which publishing and information companies can measure the success of these initiatives? What key performance indicators (KPIs) should they track?
Essentially, the metrics have to be rooted in value creation. For example, the number of new products which have been launched, sales retention, attrition and churn, retained revenue and new revenue are all good indicators that the company is working in the right direction. It's also always useful to get qualitative feedback which helps to explain those numbers and give you insights as to what the most valuable next developments might be.
What advice would you give to companies that are just starting to explore this strategy?
The biggest tip I can give is to start small and specific. Pick the most valuable user need you can support and build out from there. Make space to learn and evaluate as you go, otherwise you can end up pursuing a dead end, or at least something that is less impactful than it could be.
Can you point to any emerging technologies or trends that are likely to influence the future of content and data asset blending in the publishing and information industry?
Gen AI and LLMs are going to have a huge impact here, lowering the barriers to experimentation and therefore speeding up the pace of innovation.
In addition, customers are being trained by products such as ChatGPT, Google's Bard, and Bing Chat to query something using natural language and receive insightful answers. This behaviour is going to push information companies to keep up, with user expectations moving considerably over the next few years. Indeed, companies are already responding to this new need - 63% of information services leaders surveyed by Outsell this year reported they were exploring customer-facing product enhancements like natural language search. But they also have an opportunity to leverage the value of their carefully curated and validated data and content in a world where Gen AIs trained on the rest of the internet can be incredibly smart but also untrustworthy.
CASE STUDY: The Economist Intelligence Unit
When it comes to insightful content and must-have data, you don't get much more vital than The Economist Intelligence Unit. As you'll see from our case study, they knew they had all the right components for a new digital product that put users at the centre of its development and combined the wealth of data, analysis and insights at their fingertips into one integrated solution. Read on to find out how their partnership with 67 Bricks led to the creation of EIU Viewpoint.
NEWS: Track Record Global partners with 67 Bricks to bring enhanced solutions to their users
Track Record Global (TRG) provides its major retail clients with software and expert assessments so that they can demonstrate they are meeting their environmental, social and governance commitments. In collaboration with 67 Bricks, TRG aims to create a more dynamic system with extra functionality that better caters to its users’ needs. Read on >>>
NEWS: 67 Bricks launches six new technology consultancy options
领英推荐
We have launched six new consultancy packages to help information companies maximise the value of their content and data. For business leaders grappling with critical strategic questions, they offer concrete solutions to measurably increase efficiencies, identify opportunities to drive new revenue through new products, and quickly test ideas before investing fully - including leveraging AI to achieve their goals. The packages provide a wide variety of support, delivered in a way that ensures the most effective outcomes for 67 Bricks customers.?
WEBINAR: Technology as a Growth Driver
Our CEO, Jennifer Schivas, is chairing an insightful discussion with Emma Vodden from Bone & Joint and Andy Noble from IWSR on how they've pivoted their technology choices into being a driver for growth instead of purely a cost to the business. We'll discuss:
Breaking Down Technology Siloes for Seamless Integration: A CEO's and CTO's Guide
One of the challenges of providing a seamless data and content experience for customers is the siloes built up internally. Often, data sits within one team, journalistic and editorial content in another, with education content perhaps in a third. Breaking down these internal barriers is often one of the earliest steps companies need to take in order to provide an integrated product. But internal structures are notoriously difficult to change, and many leaders find it takes up too much of their limited time and energy. Here, we offer our thoughts as to how you can get started, maintain momentum, and break down those internal barriers for good.
1. Establish a clear vision
The journey to integration begins with a well-defined vision and strategy. Leaders should collaborate across their businesses to articulate how technology can enable business goals. The best way to do this is to create a technology roadmap that aligns with the organization's objectives, outlining the need for integration as a strategic priority.
2. Communicate and collaborate
Siloes often result from a lack of communication and collaboration between different teams and departments. Encourage open channels of communication, break down physical barriers if necessary and possible, and foster collaboration through cross-functional teams, workshops, and knowledge sharing.
3. Assess your existing infrastructure
To integrate effectively, you must first understand what you're working with. Conduct a thorough assessment of your existing technology infrastructure, including software, hardware, and data systems. Identify redundancies, inefficiencies, and gaps that hinder integration. It might be useful to engage an external consultancy to provide an unbiased eye.
4. Define use cases, experiment and refine
For efficient development, it is vital to define clear use cases at the very start that can be kept front of mind throughout. This extends to any plans to de-silo an organisation. By creating use cases you will better understand how your data should be reorganised to work smarter for you and then be able to plan accordingly. This also provides a way to measure whether or not you have actually achieved your goals, as opposed to it appearing to get it done with little real change.
4. Invest in a unified data strategy
Data is at the heart of integration. Establish a unified data strategy that defines how data is collected, stored, processed, and shared across the organization. Ensure data quality, security, and governance to build a strong foundation for integration.
5. Choose (or build) the right integration tools
Select or create integration tools and platforms that align with your organization's needs. Consider APIs, middleware, and integration platforms that offer flexibility, scalability, and ease of use. Assess whether the tools can adapt to future needs as well.
6. Empower IT teams
Provide your IT teams with the resources, training, and autonomy they need to drive integration efforts. Encourage them to explore innovative solutions, embrace best practices, and actively participate in strategy development.
7. Embrace cloud technologies
Cloud computing can be a game-changer in breaking down siloes. Cloud-based solutions facilitate accessibility, scalability, and flexibility, enabling seamless data and application integration. Consider transitioning to the cloud or expanding your cloud infrastructure.
8. Standardize processes
Standardizing processes and workflows can simplify integration. Encourage departments to adopt common practices and standard data formats. This consistency fosters smoother integration efforts and makes it easier to share information.
9. Monitor progress and KPIs
Track the progress of your integration initiatives using key performance indicators (KPIs). Establish clear metrics to measure the success of integration, such as reduced response times, improved data accuracy, or increased collaboration.
10. Foster a culture of innovation
Breaking down technology siloes requires a shift in organizational culture. Encourage a culture of innovation and continuous improvement. Recognize and reward employees who actively contribute to integration efforts.
11. Make space to learn from your mistakes
Integration is a complex process, and setbacks are almost inevitable. It's crucial to view these challenges as opportunities for growth. Learn from your mistakes, adapt your strategies, and persist in your pursuit of integration.
12. Seek external expertise
If your organization is struggling to overcome technology siloes, consider seeking external expertise. Consultants or industry experts can provide fresh insights, best practices, and guidance on how to navigate integration challenges.
If you're looking to increase collaboration within your company, or want to start creating a combined data and content product but don't know where to start, get in touch. We'd be happy to help you get started.