Enhancing research loyalty with data

Enhancing research loyalty with data

When it’s time for a research publisher to renew a subscriber account,
good quality user data can play a critical role.

An account manager who can establish what content has been accessed by users – and their engagement levels – is well-placed to accurately convey to the customer the value of the service they enjoy.

Creating loyalty through understanding

For many publishers, however, establishing even basic usage data can be a challenge that ultimately does nothing to aid the renewal process or boost understanding of the users.

Yet if these challenges can be overcome – and a supply of good quality user data established – a publisher will have the tools needed to help boost engagement and improve customer retention.

In this short guide, we examine three key challenges facing account managers as they attempt to use analytics to establish critical insights and build customer loyalty.

Challenge 1: Faster, easier, and more usable data

A research organisation looking to extract insights from usage data can be negatively impacted if the process to extract them is manual or slow. For data to play a fundamental role in the development of a research business, access needs to be quick, easy, and automated.

Better flow

Improving the ‘flow’ of information can increase use, but this alone won’t herald a data rich age. Information also needs to be presented in a way that helps establish insights immediately.
That means providing the ability to view stats from an account and user perspective or to easily switch to review usage by topic and/or content category.

Visualizing data

Whatever data is sought, it’s a must to display this via a dashboard that summarises activity and enables more considered investigation. Account managers don’t want to rely on asking colleagues for stats, to wait for them to arrive, then be forced to format them in a spreadsheet before they make any sense. Account managers need immediate access and insights.

Challenge 2: Refocus on engagement

Data provides insights that help forge closer ties with customers, but often they’re only used to review client performance or to demonstrate value ahead of a contract renewal.

Usage of this kind is, of course, vital; but if data is only used in this way then a fundamental part of its potential is wasted…

Re-engage to retain.

Regularly reviewing usage stats can help account managers identify, at an early stage, poorly performing accounts and disengaged customers the publisher is at risk of losing.

Sometimes the limited usage challenge is the result of poor data. If the only available stats come from the CRM system, they’re unlikely to have the necessary depth to help identify a disconnected customer.

If detected early, the opportunity exists to turn a disenchanted user into a satisfied customer; but to do this account managers need to be empowered with tools that provide real insights.

Challenge 3: Standardisation

What to measure and report

Usage stats can establish the strength of a publisher’s customer relationships and help identify opportunities for improvement, but none of this is possible without a structured approach to data gathering.

Statistical performance highlights aren’t enough: standardisation is critical. That means a common set of datapoints regularly gathered and reported to help an account manager understand, at any given time, what content is most compelling, what isn’t working, which users are most compelled, and those that are not.

Establishing and reporting even basic datapoints like this can help account managers to accurately establish customer insights that, in turn, can drive their business forward.

As the developer of a leading SaaS research publishing and content management platform, Publish Interactive is well-placed to help research firms maximise their relationships with customers.

How can AI enhance research firms’ customer relationships?

AI is already enhancing customer relations for multiple business sectors – can it do the same for research?

Organisations of all types are rushing to understand how Artificial Intelligence (AI) can enhance their customer interactions – and the research community is no different.

AI focused

In a previous post, we looked at two examples of how AI is being used in the research-gathering part of the sector.

Naturally, this is where much of the conversation and industry focus is pointed but what happens when that market intelligence has been compiled and it’s ready to be made public?

Can AI maximise the opportunity to get relevant information in front of the right people and, furthermore, handle various aspects of a business’s relationship with its customers?

What can research businesses learn from the ways in which AI is being used currently by other organisations?

Email subject lines

Virgin Holidays is using AI technology by Phrasee, a UK startup, to automate headline writing for its marketing emails. According to reports, the machine-powered scribe outperforms humans by up to 10% in terms of open rates.

Those incremental improvements can be worth a significant sum to a multi-million-pound business. The technology also allows the holiday company to test more options and save time in the long-term.

Fraud detection

Online supermarket Ocado is using machine learning to detect incidences of fraud as people navigate its website and apps. Every time a customer adds trolley items, books a delivery, and goes through the checkout, they leave information behind. This information can be very useful.

Ocado Technology, the team developing software and systems for the online grocer, applies machine learning to find ways to predict when fraud might occur and to differentiate this from normal customer activity.

It does this to prevent customers being adversely affected by fraud and to prevent fraudulent activity spreading, but this isn’t the only way the online grocer uses AI in customer relations.

Machine learning is also used to power the way it recommends products and generates search results. For example, it claims to have designed systems to avoid suggesting meat to vegetarians or products containing gluten to celiacs.

Virtual customer service

Customers of the Royal Bank of Scotland and NatWest have been interacting with a virtual chatbot for almost a year and a half. It picks up queries when messenger conversations start and attempt to deal with the issues that come its way.

Powered by IBM’s Watson technology, the Luvo virtual agent interacts with customers to perform basic tasks. Anything complex is left to a human.

After a successful trial with RBS’s staff, Luvo went live in October 2016. It has the ability to answer ten questions and the capacity to learn to deal with more complex issues. It even recognises whether a customer is unhappy or frustrated, and can change its tone appropriately.

The technology was put into use to free up the time of the bank’s human advisers. While the chatbot deals with simple queries, the bank’s relationship with its customers is enhanced by having staff dedicate more time to helping customers with complex issues that require a level of empathy of which computers aren’t currently capable.

Complex uses

As we have indicated, in some areas, technology might simply prove to be more efficient than humans at performing key tasks. Other implementations could see AI-powered systems add value in ways humans previously didn’t or couldn’t. However, as our banking example shows, the effectiveness of customer relations could also be enhanced by the combined use of technology and humans.

Just in these few simple examples, we can see how the implementation of AI across the economy is likely to be complex and multifaceted – and this variety is likely to be reflected in how research firms use AI in their customer relations.

If you’d like to know how technology could enhance your research business please call, email, or sign up here for a demo of our industry-leading content publishing and management system.

Infographic: Our five-year journey toward fully-automated site updates

It all started with a four-hour meeting in Starbucks, and the result was a plan to move Publish Interactive towards fully-automated updates over five years…

As we’re four years through that journey, we thought it would be good to show you the progress we’ve made, the benefits brought, and what the next year is going to bring.

If you’d like to know how continuous deployment could help your business please call, email, or sign up here for a demo our industry-leading content publishing and management system.

These two uses perfectly show how Artificial Intelligence can shake up research

The focus and determination to make use of Artificial Intelligence (AI) is red hot across all industries. While some race ahead, others like the research sector are watching these early adopters and learning valuable lessons that could help inform their own implementation plans.

Technology and, particularly, the retail sector have been quick to make use of benefits offered by different forms of AI.

Apple’s Siri is a ubiquitous form of natural language processing (NLP) that interprets voice commands and responds accordingly, while online retail often involves automated chatbots supplying customer support.

New business

A study from Boston Consulting Group examined the appetite for AI across businesses. It found that 75% of executives believe AI will enable their companies to move into new businesses.

The research also suggested that almost 85% believe AI will allow them to obtain or sustain a competitive advantage, while more than 60% said a strategy for AI is urgent for their organizations.

Desire is high, but the gap between appetite and execution remains significant. The Boston Consulting study found that just one in five companies has incorporated AI into some offering or process, while just one in twenty has extensively incorporated AI.

AI in research

Within the research community, the need to incorporate AI is understood but use or experimentation are not yet widespread.

A lack of widespread experimentation, however, doesn’t mean there’s no experimentation. In fact, there was a conference last year on this very subject (recordings of the sessions can be found here) and there are several organisations making waves in research with AI and a string of other interesting applications.

One application highlighted in a research paper by InSites Consulting looks at the use of predictive analytics to ensure that market research communities and consulting boards are not disproportionality influenced by strong characters who might skew research outcomes.

Looking further afield, Prague-based response:now is an organisation doing impressive things. It supplies automated market research that creates reports based on machine learning. It already works with Google, Mastercard, and McCann.

Fred Barber, Managing Director of response:now in North America, explained his business’s proposition to Martech Today – 75-80% of the current effort in market research, he said, is in writing the reports.

“It [writing] is costly and time-consuming,” he said. In comparison to traditional research, response:now can deliver in “five days, not five weeks and for 2K instead of 20 (on average).”

So, that’s a heavily increased speed at a much-reduced cost. In those terms, market research can become much more every day. It is something actionable and relied upon by managers and workers, rather than accessed mainly by executives who may or may not build it into strategy.

Next moves

Even in the two simple examples we’ve highlighted, it’s possible to see how AI can be a disruptive force in the research industry.

Our examples show how research production could be altered, but what we haven’t really touched on (and it’s a subject to which we’ll return to) is the effect AI is likely to have on the way research businesses interact with customers.

Before signing off, we just want to highlight a key finding from a recent 451 Research Study on Current and Future State of Artificial Intelligence and Machine Learning. It says machine learning is set to be the most transformative technology existing over the next decade. It also says that we are approaching an inflection point at which companies that have not integrated machine learning into their offerings will fall behind those that have.

To remain competitive in the research sector, it looks like executives might have to get to grips with a lot of new ways of interacting with the customer…

If you’d like to know how technology could enhance your research business please call, email, or sign up here for a demo of our industry-leading content publishing and management system.

6 ways tech binges are encouraged – and 1 excellent reason why you’ll never binge with Publish Interactive

Poorly-designed technology can be bad for you, but even more concerning are the platforms designed to keep engagement high at all costs – often without the users’ best interests at heart.

Features aimed solely at retaining our engagement will be familiar to most people:

  • Newsfeeds that auto-refresh and scroll endlessly
  • Countdown clocks and auto cueing for video playback
  • Rewards handed out for continuous chats
  • Flashing dots that tell us a contact is preparing a reply
  • Read messages that tell you a conversation is progressing

Addictive tech

From just six bullet points, it’s easy to understand how platforms can encourage addiction and how individual users start to develop bingeing habits. So much so, that those who helped create these technologies are now speaking out against their effects.

Binge free

The platform developed by Publish Interactive isn’t one where a user is likely to binge. For a start, none of the addiction-forming features mentioned is found across the technology; but beyond that, the product is designed to allow users to quickly find information that answers their questions.

Given that our software is a business tool aimed at improving the effectiveness and efficiency of its users, the idea of retaining them simply for retention’s sake seems would be counter productive.

Publish Interactive produces smart technology designed not to disrupt your work life, but to enhance it at the point when you need to quickly access high-quality business information.

It doesn’t need you to be there, it’s there for when you need it.

If you’d like to know how this technology could enhance your work life please sign up here for a demo of our industry-leading content publishing and management system.

Analysts are rock stars – let’s make it easier to find their content

Analysts are fundamental to the success of research businesses. Their insights cut through billions of lines of data and deliver a clear vision of various business sectors. It’s time to make more of them.

Use of smart publishing technology is a great way for a research business to reinforce the expertise of its analysts. Let’s use it to empower these gurus of business intelligence…

Analyst = rock star

Market analysis firms have historically been reluctant to give great prominence to their analysts or use them heavily as marketing assets. As a result, analysts tended to remain in the background.

Today’s business climate is different. It’s increasingly open. Analysts have Twitter accounts, they blog, and they’re likely to be active on LinkedIn. As organisational credibility is so much more focused on personality, it makes sense to harness the public value these key individuals already possess.

Tech that empowers

Intuitive technology enables customers to find out more about individual analysts and makes it easier to quickly access the content they produce.

People naturally gravitate to people they trust. If a user has found value in the work of an analyst, technology can be used to empower the reader to find even more of their output.

Going public

A smart publishing system should empower analysts to brand themselves as the heroines and heroes of their subject matter – and the best way to do this is to place their profiles front and centre.

A good profile should list the analyst’s name, their job title, and the sectors they cover. To help put a face to the brain, profiles should also carry a photograph and biography alongside a list of all the content that individual has produced.

Boosting profiles

In a recent update to our publishing platform, we made it possible for research businesses to add features that would help raise the profile of their analysts and make it easier for customers to locate their content.

Version 7.9 launches with loads of analyst updates

These included:

Analyst landing pages – where a full profile could be displayed

Search by Analyst – enabling users to find a specific analyst by entering their name in the search bar. What’s more, if they’re listed, their name will appear as an auto-complete option as the user types.

External landing pages – we also made it possible to link to an external analyst landing page so publishers can direct users to profiles lying outside any password-protected content area.

Search filters – we even created an option where ‘Analyst’ can be added as a search filter so that users can even more quickly find content from the people they trust.

Making it happen…

Through a series of relatively small measures, we’ve empowered our customers to make their analysts the cornerstone of their digital marketing efforts.

It makes perfect sense and is easy to implement – all it requires is for a research provider to use the right kind of publishing technology.

If you’d like to see how profiles of your analyst would look on our industry-leading content publishing and management system please call, email, or sign up here for a demo.

7 huge losses if you fail to track how your research content is used

If you’re creating expensive research then only making it available to customers via an emailed or downloadable document, there’s no real way to accurately know what happens next – in today’s customer-centric economy, this isn’t good.

Equally, if you provide a subscription that allows a customer access to your portfolio without you trying to understand how and why they use your content, you’re practically throwing away valuable information that could be critical to the future direction of your organisation.

So, what information could you be missing out on and why is that bad for business?

1. Who is viewing the content?
If an admin assistant bought a report then immediately passed it to the Insights Director, do you really want to try and engage the assistant in future? How do you think they’ll respond to marketing and sales? Perhaps not as well as the person who’s consuming your report. But how would you know that?

2. How many people view it?
Is it just the individual who bought it, their whole team, or also people working in another business? If you don’t know, then you have no idea about your potential market. How many separate accounts, license holders, or one-off purchases are you missing out on?

3. How many times is it viewed?
Imagine you sell the same person two pieces of content, but you don’t know that they looked at one piece just once and the other more than 100 times. Without this information, you’d assume they’re equally interested in both subjects. Think how different your sales and marketing approach could be if you knew, in detail, how many people looked at which report?

4. Which sections are interesting, which aren’t?
If you sell someone a report about meat sales and they only read sections related to pork products, how would you know they have no interest in beef, chicken, or lamb? You wouldn’t. As a result, your sale of future content to them will be less precise.

5. How do you make your content relevant?
Without usage data, it will be difficult to create personalised content bundles for customers as you won’t know what they’re interested in. Also, if you can’t gather usage data to find out how content is used by the entire userbase, it will be difficult to know what subjects the audience is interested in and then set an appropriate strategy for future research production.

6. How do you renew subscriptions?
Let’s see: you have no real information on how often your content was used, nor by how many people, and you don’t have figures for all the people in a single organisation that read your expensively-produced research – nor the breadth of topics these people were reading. Can you still make a convincing case for maintaining the same fees? Can you justify a suggestion to expand the account license to include new content, new topics, and new categories that might be of interest?

7. How do you sell additional content?
The answer is: you can still sell it, but you won’t have any information to back up your claims or to ensure it’s relevant to the person you’re selling it to. Now, just imagine approaching the same call knowing their three major topic interests, and armed with an offer for additional content in this area at a cutdown price. Those are two very different scenarios.

If you need to track content usage, we can help.

Either call or email for a chat or sign up here for a demo of iReports – our industry-leading content publishing and management system.

How usage data helps turnaround disengaged customers

Market Intelligence providers can analyze usage data proactively to justify a renewal or to formulate a new strategic content plan.

However, that’s not the only way it can be used; data of this type can help turn around disengaged customers.


If several months into a new contract, the data shows the provider that several users are engaging infrequently, using little content, or not logging in at all – they can be proactive about it.

This is where a salesperson or account manager can really earn their corn:

  1. Contact these individuals
  2. Find out what is limiting their involvement
  3. Review their content, or offer training to help
  4. Arrange a call to deal with their problem

By monitoring users who are not responding to content and then getting in touch to see what’s wrong, smart MI providers can create new fans of their service and make life that little bit easier for themselves for when the time comes to discuss the renewal of the service agreement.

Are you looking to become a smart MI provider? Want to learn more? We can help.

Sign up here for a demo of iReports – our industry-leading content publishing and management system.

‘So, that’s 200 rows of data that must be entered manually…’

The data’s great, but it’s in PDF.

Ordinarily, the analyst would screenshot this information, but it needs to be edited in Excel before putting it into a presentation.

So, that’s 200 rows of data that must be entered manually by the morning?

If you’ve ever compiled a report, you’ll understand how taking data from other sources and making it fit into your presentation can leave you wanting to weep.

In iReports, reusing data from an interactive report couldn’t be easier…

  • Find and filter the data you need
  • Click to add it to your Clippings
  • Export to a pre-branded PPT or Excel file (along with all necessary attributions and notes)
  • Download the file or share it with colleagues in the platform

All the data you need, where you need it, in minutes, not hours…

Want to find out more about iReports? Either call or email for a chat or sign up here for a demo of our industry-leading content publishing and management system.

Categories & Tags: what’s the difference? (let’s end this confusion now!)

Categories and tags are used widely across iReports, but for many their use is confusing; after all, don’t they both just do the same job? Well, not quite. It’s time to end the confusion…

Categories relate to a report’s subject. For example, a report about drugs used to treat bronchitis would be found in the ‘Respiratory Disease’ category. Categories are used to bundle related pieces together and make it easier for publishers to sell packages of linked material. They also make it easier for users to find information.

Read four tips for making the most of Categories.

A category relates to the subject and is used to organise and sell research. Tags, however, are used to detail all the elements that are mentioned within a report.

Tags apply across all categories. As a single report will mention many different topics, it’s likely to have multiple related tags. For example, our report about drugs for treating bronchitis might have all the companies it mentions listed as tags to help users find related content.

The reason we have both tags and categories is that it would just not be practical for tags to do the job that categories do. Categories help us apply necessary structure to content enabling us to order it into deep hierarchies.

Read about using Tags.

Read five tips for making the most of Tags.

Want to learn more about Tags and Categories? We can help.

Either call or email for a chat or sign up here for a demo of iReports – our industry-leading content publishing and management system.