What makes a cracking conference?

April 26, 2012 – 10:43 am

Conferences are an excellent opportunity to connect with others in the same industry, and in publishing at least there’s a busy annual schedule to choose from. This month we’ve been planning for forthcoming events, which got us thinking about what we liked most about those recently attended, and what sets apart a really successful conference.

1. Compelling speakers. An interesting programme with a great line-up of speakers sits at the heart of every good conference. So what makes for an effective talk? It can be tricky to get the balance right to avoid losing the audience in too much detail, but focused topics which address real day-to-day issues generally work well. In contrast, themes which are too broad, vague or ‘future gazing’ to the point where they have no real substance should be avoided. Similarly, talks which amount to a thinly veiled sales pitch for the speaker’s product or company are unlikely to win over a seasoned audience.

2. Programme gaps. Whilst engaging talks are important, it’s equally key to allow enough time for meetings and networking in-between. Big conferences have an international draw, and can be one of the few opportunities in the diary to get influential industry players together in the same room. This means that a lot of the value from attending comes from the meetings you can arrange in advance and chance conversations on the day.

3. Event communications. A fantastic venue is always a great asset, but since many in attendance will not be familiar with their surroundings, strong communication about the local area (where to find it, nearby hotels and restaurants) and the conference schedule (start times, registration, programme etc) is vital. This might be supported by a well designed conference website, and informative email communications with attendees in the run up to the event. Enthusiastic and helpful staff on the day can also make all the difference.

4. Free stuff! Everyone likes freebies, and complementary items such as mugs and T-shirts, plus giveaways and competitions can help increase the overall ‘feel good’ factor of the event. Perhaps most importantly of all, free alcohol in the early evenings is widely appreciated and helps to bring everyone together at the end of the day for further informal networking.

5. Reliable wi-fi. With many attendees needing to keep on top of email and work, plus tweet and blog about the conference itself (occasionally all at the same time!), access to reliable wi-fi is vital. In our own case, we often wish to give online demos of our core product MasterVision to interested parties, and so slow or unavailable internet can be a major headache. As a general issue we’ve found internet problems to be the number one conference ‘gripe’, so it’s a fundamental point to get right.

By DataSalon | Posted in Publisher Marketing | Comments (0)

Data mining for new markets

March 22, 2012 – 9:15 am

As scholarly article output has continued to grow at an exponential rate from emerging territories such as China and India, so author submissions to your books and journals have probably grown too. This makes it increasingly vital to capitalise on your expanding author network and all the associated institutional data that it brings with it.

However, sales into these new areas can often show less impressive growth. So, what tactics might you employ to address this disparity? Your first thoughts might be to work with outside agents and third parties to do the leg work by using ‘their’ contact network; you might choose to use local language speakers and/or telesales services; you might even go for locally hosted server networks. These can all produce results, but in addition, don’t overlook your own data when considering your options.

Whether you know it (or can easily get to it) or not, you probably have many sources of customer intelligence which can be applied to this problem. By using your data first, you can achieve better visibility of your customers and better control over the prospecting process.

1. Data, data, data. As a part of your everyday business of providing online access to content, what you have in abundance is data – data about your customers. This is likely to include information about usage, author submissions, subscriptions, registrations, TOC alert sign-ups and more. Now, more than ever, this data needs to be made to work for you.

2. Dig in. Once your data is organised and integrated, you can mine it for meaningful, targeted and qualified prospecting. Identifying institutions with high author submissions but low (or no) paid subscriptions may be one way to target new sales prospects. Other sure signs of ‘hot prospects’ include high numbers of signups for free alerts, or high numbers of ‘access denied’ events indicating unmet demand for your content.

3. Understand your customers. Crucially, you can establish direct relationships with customers, ‘old’ and ‘new’, allowing you to cater directly to their needs. Analysing usage and market sectors can potentially improve content relevancy, sales growth and retention. Adding the ability to cross-reference your institutional data with third-party databases such as Ringgold adds further value by enabling you to track your overall market share within new territories.

4. Take control. By working with your own enhanced customer data, you can get additional visibility of sales efforts and the returns you are getting from your sales expenditure. No more questioning whether your sales activities in new markets are paying dividends – you’ll be able to track over time all the key ‘health indicators’ of subscriptions, usage, article submissions, etc.

So, in conclusion: good customer insight means you are not leaving sales to chance, and can make the best use of your existing customer intelligence to help drive growth in new markets.

By DataSalon | Posted in Customer Insight, Publisher Marketing | Comments (0)

Measuring social media marketing

February 28, 2012 – 10:17 am

There was an interesting article in Marketing Week this month which neatly exercised most of the usual arguments around social media marketing. The article cited a survey suggesting social media had “little or no value when acquiring new customers“, adding it was “difficult to justify investment“, and that any measure of return usually went no further than “fluffy metrics“.

The comments posted in response covered the usual counter arguments: it provides “support to other channels” and helps “drive customer engagement” through a “two-way dialogue“. The themes of “we believe!” vs “we need proof!” begin to give the whole debate a strong whiff of faith vs reason.

While this was a general article not specific to academic publishing, the same points apply equally well to social media marketing in our industry. There are some strong advocates, and the topic certainly gets a good share of air-time at industry conferences and probably at internal marketing meetings too, while hard evidence about the financial benefits does remain understandably hard to pin down.

So in what ways can social media marketing be measured? We’ve taken a brief look at the “big two” channels of Twitter and Facebook, and suggest some basic metrics which publishers engaged in social media activities can easily track and assess:

Output: As a crude measure of how much ‘effort’ you’re putting into social media, keep count of how many Twitter tweets and Facebook posts you’re creating. Many publishers run separate accounts for different subjects, brands and titles, so those different routes should all be counted up. Quality is more important than quantity of course, but if you’re paying staff or agencies to maintain your social media presence, it makes sense to keep tabs on how many messages are being posted each week.

Readership: You can see a total count of ‘Followers’ on Twitter and ‘Likes’ on company/brand Facebook pages, providing a rough indication of readership. It’s useful to compare that figure to known contacts from non-social-media activities such as online signups, subscription sales, and author submissions – if you have 1 million ‘traditional’ email contacts and 5,000 combined Twitter and Facebook readers, it probably makes sense to consider those proportions when allocating your marketing resources.

Impact: Here we get to the heart of the real value of social media, and things get a little trickier to pin down. Blasting out news about your new journals and article highlights is one thing, but are you getting the desired “customer engagement” and “two-way dialogue”? A one-way conversation does not make the best use of social media, so low engagement might require a re-think of the type and/or frequency of messages posted.

  • Facebook helpfully provides a headline figure for “People talking about” your content in the last 7 days, counting a range of interactions such as ‘likes’, comments, sharing, etc. This serves as a reasonably good headline score for your Facebook impact.

  • On Twitter, ‘impact’ could include replies, retweets, favourites and mentions. Twitter itself doesn’t offer a single overall score for all of those, but it does enable you to tally them up yourself (via the @Connect section) and there are also various third-party services which claim to do that for you. It’s also useful to count your own direct replies to individuals: another indication of how “two-way” your interactions currently are.

To conclude: using some simple numeric metrics for social media marketing, you can track:

  • if your ‘Output’ is appropriate to your social media spend;

  • how your ‘Readership’ compares to other marketing channels; and

  • if your ‘Impact’ demonstrates two-way customer engagement.

There is clearly much more you could measure, but basic scores like these can provide a good starting point for publishers seeking to quantify the value of their social media activities.

By DataSalon | Posted in Publisher Marketing | Comments (0)

What does Open Access mean for marketing?

January 26, 2012 – 10:39 am

Subscription data normally sits at the heart of a publisher’s view of the customer, because it’s crucial to know who has paid for what. But, the same rules don’t apply to Open Access (OA) journals, whereby content is made available for free and a publisher’s revenue stream comes instead from an ‘author pays’ model. Let’s take a look at the various ways an OA model might change your marketing activities:

1. The Author is King. In a model where authors pay you for your peer review, content production and distribution services, accurate author data displaces subscription information as the most critical information source. You might already be analysing data from your manuscript tracking system, but does it include details relating to each author’s submission history and publishing outcomes, author interests, and also editor activity? You’ll want to ensure that every drop of author information is available to your staff for searching, segmentation and analysis.

2. Follow the Money. Who is paying you to publish OA content? It might be the authors themselves, or more likely their research funders. These could be academic institutions or other organisations already known to you as paying subscribers, but it’s possible there could be gaps in your knowledge here and further research to capture the details of all potential funders might be necessary. Of course, wherever possible, you will also need to know the connections too, ie. which authors are related to which funders?

3. Who’s Who? With author and funder records taking centre stage, the need for standard names and common identifiers becomes critical. An author’s name is a poor basis for identification because there are so many different authors who share the same name. The ORCID initiative which is aiming to solve the author/contributor name ambiguity problem in scholarly communications, is very relevant here, and it’s likely that this ID will soon become a must-have field in every author or manuscript database.

4. Article Usage. Usage is another data source that you may already be including in your single view, but your statistics are probably only at the journal level and integrated from an institutional perspective. Clearly, high institutional usage remains important to satisfying existing authors, attracting new authors and enhancing your brand overall, but you will now need to provide authors with statistics on the performance of their individual articles. The PLoS article-level metrics are interesting food for thought here. Your single view should therefore be capable of segmenting on usage at the article level too. In this context, the PIRUS projects and a new COUNTER standard for journal article usage are also very relevant.

5. Data Mining. You will want to include and explore any data source that might lead you to new authors, as ‘prospecting for new authors’ replaces ‘prospecting for new subscribers’ as a key sales and marketing priority. This might draw on data sources already at hand (eg. alert recipients, society member records) but it could also be sources not yet on your radar, such as conference proceedings or third party resources listing authors and their past papers or interests.

In summary: it’s clear that OA publishing can turn a lot of current journal marketing practice on its head. Any publisher involved in OA publishing should therefore give careful consideration to all of the issues highlighted here, and consider taking steps to ensure that all the relevant data is being captured and made available for author-based analysis.

By DataSalon | Posted in Publisher Marketing | Comments (1)

Seasonal thoughts about… turnaways

December 13, 2011 – 1:34 pm

I know the subject of ‘turnaways’ doesn’t sound very festive, but there is a tenuous link: Mary and Joseph became very early turnaway statistics themselves when they were told there was “no room at the inn”.

The definition of a “turnaway” is as simple as that: wanting to gain access, but being turned away at the door. In terms of online content, whenever a user tries to access an article but hits the paywall and fails to get there – that’s a turnaway.

Now – to continue the seasonal theme a little longer – many sales people could probably think of no better gift than a list of hot sales prospects, each backed up with hard evidence of demand for the content they are selling… and that’s exactly what turnaway analysis can provide.

While you might consider failed access stats an uninteresting by-product of your access platform, they can provide hugely valuable insight into customer demand.

To take an example: let’s imagine that 50 researchers at the University of Life tried and failed to access articles from your new title ‘The Journal of Hamster Dentistry’ last month. Even though those users probably weren’t identified individually, somewhere in the logs their IP addresses will have been captured.

It’s then possible to trace that IP information back to the relevant university: either using your own subscriber IP data (if the University of Life already buys other titles from you), or else through third-party IP range data (eg. via Ringgold).

With the detective work done, the gift of a hot lead is ready to wrap up and deliver to your sales team: clear evidence that there’s significant, current demand for that journal, making a compelling case for taking out a subscription.

With budgets squeezed on all sides, this kind of evidence-based selling is increasingly important, to ensure that sales efforts are targeted in the right places. It’s also pretty easy to set up (via MasterVision naturally). So, if you’re not yet using turnaways analysis as a key part of the sales mix, then consider making it a resolution for 2012!

By DataSalon | Posted in Customer Insight | Comments (1)

The secret lives of lists

October 27, 2011 – 9:38 am

Lists appear everywhere on the web: most commonly as bulleted or numbered text and within dropdown form fields. This comes as no surprise, because lists are a great way of helping users make sense of complex information. However, as with many things that seem simple at first glance, they can pose their own set of tricky challenges once you look beneath the surface.

Let’s start with ordering: that’s easy, right? Well, not always. Alphabetical sorting works well in most cases as that makes the values easily scannable by eye. However, this is surprisingly tricky to get right – we’ve all seen lists with accented words all sorted to the bottom, or quoted and ‘junk’ values with odd characters dominating the top. There’s also the issue of mixed letters and numbers to think about: a standard alphabetical sort will place ‘Package 11′ before ‘Package 2′, which would require some custom rules to make the order more ‘natural’.

Even with these issues addressed, alphabetical sorting is not always best of course. A list of months of the year beginning ‘April’, ‘August’, ‘December’ is not easy to work with, and in other cases it might be more helpful to order values in terms of importance or popularity. A lengthy list might also benefit from being broken up into sections with headings, although that raises the question of how to order the sections themselves as well as the items within them. And so there are more and more decisions to make just to make a list “feel right” to your end users.

In other contexts, users can themselves influence ordering, as when clicking on column headings within data tables. And arguably, of course, tables can be seen as a ‘special’ type of list which present some unique challenges of their own. Here, long values within cells can be a problem, requiring truncation, horizontal scrolling of the table, or both. In particularly tricky cases, a list can itself occur within a cell, making the containing row “too tall” unless more rules are added to address this. In addition, the number of table rows can get very large (think search results), so requiring the ability to ‘page through’ results.

But there are also extra opportunities here: as well as enabling a simple way to re-sort items via a clickable header, tables can also offer the ability for users to choose which items are displayed at any given time. For example, it may be desirable to only show rows relating to a specific product or year, both of which can be achieved via column filters similar to those seen in Excel. With the issues above addressed, and users having full control over both ordering and filtering, a table can therefore represent an extremely flexible way of handling complex lists.

By DataSalon | Posted in Technology Topics | Comments (1)

Top tips for bad customer service

September 22, 2011 – 9:53 am

Many of the companies we deal with personally provide astoundingly bad customer service (phone, mobile and utility companies: we’re looking at you). Well, they say if a job’s worth doing badly, it’s worth doing really badly – so here are 5 top tips for companies who truly wish to excel at bad customer service.

1. Don’t provide the product/service you’re being paid for. This is really the basic foundation of all customer dissatisfaction. Any aspiring bad service market leader must go out of their way to ensure that deliveries don’t arrive and services are provided intermittently. Note that intermittent provision of a service (eg. broadband) is actually preferable to not providing it at all: it gives much more scope for nurturing customer irritation.

2. Make it really difficult for your customers to talk to you. For maximum impact here, you should first spend millions on branding and advertising to tell the world what a friendly and helpful company you are. Then, ensure that your paying customers are unable to speak to you in the event of a problem. There are two tried-and-tested techniques for this: the automated phone menu gambit, and the you-can-only-contact-us-by-email-which-we’ll-ignore stratagem. Both are proven to provide excellent motivation for customers to tell all their friends how very bad your service is.

3. Blame the customer. If you do have the misfortune to find yourself actually speaking to a customer, do all you can to insist that nothing is wrong. In doing so, it’s good practice to imply that the customer is lying, for example by stating that the delivery “definitely arrived last Friday”, or that mobile coverage is “excellent in your area”. If the query relates to a computer, always imply that the customer is at fault and then say: “have you tried re-installing Windows?”

4. Stitch up your support staff. Everyone knows that a company’s success comes down to its staff, so do ensure that support staff are fully untrained and have none of the information and tools they need to do their job. Your basic disempowering checklist should include ensuring that support staff cannot see customer account details, do not understand how your company’s processes work, and have no authority to change anything.

5. Spend all your money on billing systems. While much of the bad service rulebook is about striving for imperfection, there is one very important exception: your billing systems must be built and managed with all the IT resources of the Large Hadron Collider. Money must be removed from bank accounts with ruthless efficiency, and billing errors in the customer’s favour must never, ever occur. While lightning-quick transactions are crucial in this area, don’t forget to include the feature whereby refunds always take “up to 30 days” to be processed.

And so there you have it, aspiring providers of customer service awfulness: do your worst.

By DataSalon | Posted in Customer Insight | Comments (2)

Can I talk to you or not?

August 25, 2011 – 12:53 pm

An integrated, single customer view has many benefits but it can often pose a tricky question too if your various data sources harbour different opt-in/opt-out contact permissions for the same individuals: can I talk to you or not? It’s important to address this problem, to ensure you are communicating with as many relevant people as possible, while also respecting the wishes of those who prefer not to receive marketing messages. Here’s how we have worked with some of our clients to address this challenge:

1. Let the marketing team decide. If John Smith opted out when he created his registration profile on your content site, but he opted in when he signed up as an author, you might want to keep those different choices visible. Then, when the marketing team creates a contact list for a campaign, it can consider all of those competing opt-in/opt-out filters (drawn together on one screen for easy reference perhaps) and set them appropriately for the campaign in question.

2. One out, all out. The difficulty with the approach above is that if John Smith has conflicting permissions from different source systems, then which value takes precedence? One alternative strategy is to generate a master ‘OK to Contact?’ field and then set that to ‘No’ if any one of the source datasets contains an explicit opt-out. This way you’re only ever using one field to identify who is eligible for marketing, regardless of what the message is. It’s simple and it’s user-friendly (but a “one out, all out” policy will also produce a smaller set of contactable customers).

3. Establish a hierarchy. As an organisation you may see some data sources as more important than others (e.g. member data for a society publisher). In this scenario, you might set your ‘OK to Contact?’ field based on your member data permissions first, then another source second for users with no member data, and so on. In effect that allows you to set business rules to say that an opt-in from your member data overrules an opt-out from elsewhere. While this approach is more complicated to define, the detail does not need to be exposed to the marketing users: they still see the one ‘OK to Contact?’ field and simply set it accordingly.

4. The holy grail? Rather than just finding strategies to handle conflicting permission settings for the same individual, the longer-term goal might be a single system to manage all yes/no permissions data, with an interface for customers to manage all their choices on one page. If your marketing effort is being driven by an integrated, single customer view, it makes sense to try to move away from source-specific opt-in/opt-out options for customers, as it’s this repetition that creates the issues described above. However, it can obviously be a technical challenge to do this if different parts of your front-line, customer-facing business are managed by different suppliers.

By DataSalon | Posted in Publisher Marketing | Comments (0)

Top tips for IT startups in academic publishing

July 28, 2011 – 12:19 pm

This month sees DataSalon’s 5th birthday and the anniversary of our first client (Oxford University Press) signing up for our customer insight solution MasterVision. Like any startup we’ve definitely had our ups and downs, but 5 years down the line we’re still here, and so it seems like a good time to share some insights into what works well for us:

Specialize. It took us a couple of years to fully work this one out, but it’s a smart move to specialize in one industry. From a product point of view, it means we can fully embrace all of the industry’s quirks and special problems (of which publishing has plenty, such as institutional sales and ‘big deals’). And from a sales perspective, it has helped us enormously when prospective clients feel we really understand their business, and, to coin a phrase, know our articles from our eTOCs.

Focus. We’ve worked incredibly hard over the last 5 years almost exclusively on one single product (ie. MasterVision). To give an idea of just how hard we’ve worked on the software (a hosted service which we can upgrade any time): to date we’ve averaged over 450 minor versions per year. Diversity can be a great strategy for bigger players, but as a startup with limited resources, what works is putting all of your team’s energy into doing one thing very well.

Listen. Perhaps contrary to startup folk wisdom, we haven’t tried to ‘get big quick’, and we’ve spent a lot more time talking to existing clients than we have ‘doing sales’ to potential new ones. With a subscription product like ours, it’s fairly common for IT suppliers to ignore existing customers (they’re paying you anyway, right?). We’ve tried hard to avoid that by staying in regular contact, not least because all of our best product ideas tend to come from listening to what the end users have to say.

Lead. Listening only gets you so far, because being exclusively client-led tends to produce lots of small, incremental changes. We’ve also tried to show some leadership in the overall direction of our product, by looking out for bigger problems in need of a solution. This is what led us to create various ‘hierarchy’ features, to help publishers get to grips with the issues of selling at one level (eg. a university) and how that relates at lower levels (eg. departments within that university). That’s also why we recently published the Customer Insight Framework as a way to lead a wider industry discussion on that topic.

Deliver. For a client, there’s nothing quite so annoying as a supplier saying ‘yes’ to everything when pitching, then, having won the project, explaining how everything is in fact immensely complicated. Our top startup tip: don’t do that! Tell the truth about what you can do and how long it will take, and then meet your deadlines, even if it means working weekends, evenings and nights to do so. It’s simple stuff, but it’s so often done badly within the world of IT, that getting it right really helps you to stand out.

By DataSalon | Posted in Customer Insight | Comments (0)

Why we created the ‘Customer Insight Framework’

June 29, 2011 – 9:59 am

This month sees the release of our free ‘Customer Insight Framework’ document, which we think is essential reading for all sales and marketing staff working in scholarly publishing. The framework, endorsed by 5 major publishers, presents a concise set of 12 guiding principles for a complete and fully-integrated customer view. So what were our reasons for creating it?

1. Explain why scholarly publishing is different. It’s not stressed often enough quite how different scholarly publishing is from other industries such as direct-to-consumer retail. Most books, articles, and blogs about customer marketing assume the direct-to-consumer model, whereas scholarly publishing is very different: “customers” are a complex mix of individuals, libraries, companies, universities, hospitals, and large buying consortia. This difference should be given due recognition, because it brings with it a whole bunch of complications.

2. Highlight the problems. Noting that “customer” is a difficult concept, further problems arise from this. Firstly, identity becomes a major challenge: do we consider the Chemistry Library to be the same customer as the Main University? Is it also known as the Boyle Library? Is Company X a subsidiary of Company Y, or a separate entity? And with these identity problems come real business challenges: have I already sold to Library A via a big deal? Is University B correctly restricting access only to agreed faculties? Is Company C paying an appropriate rate for its number of staff? We believe these problems are sometimes poorly understood, and often misdiagnosed as “we need CRM” (we’ve blogged in the past about the many meanings of CRM).

3. Define a shared roadmap for like-minded publishers. So, enough with the problems: how can we solve them? A core aim in creating the framework was to try to build some consensus on what the main ‘customer insight’ objectives for a major publisher should be. To that end, we consulted many of our publisher clients when drafting the document, and sought their views on the 12 key points it contains. The checklist now gives our own conversations with publishers a common focus, and highlights ‘gaps’ where pieces of their big picture are still missing. (Interestingly, it has already prompted some interesting idea-sharing discussions directly between the publishers we work with too.)

4. Sell solutions, not technology. The framework stands alone and makes no reference to our own MasterVision product, but it was of course also created with an eye to raising awareness of DataSalon’s services. As a piece of marketing, we hope it will help communicate that we are fundamentally selling ‘customer insight’ (ie. a specific solution to a real problem) not just ‘tools and technology’. We hope it contributes some thought-provoking ideas to a wider industry discussion, and helps to explain why ‘customer insight’ is such a big challenge for all scholarly publishers.

Download the ‘Customer Insight Framework’ (PDF)

By DataSalon | Posted in Customer Insight | Comments (0)
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