MasterVision behind the scenes

April 25, 2013 – 8:38 am

traceyFor our clients, MasterVision provides a sleek representation of all their customer data and gives a clear, joined-up view across multiple data sources. But much like an elegant swan on a lake, there’s more effort going on under the surface than you might think. This month, our Senior Product Manager Tracey Rousell takes a look behind the scenes at just some of the hard work that goes into making sure MasterVision runs seamlessly for its users.

Security matters

We take data protection and security very seriously. Our web servers are kept fully up to date with the latest software, and we monitor them daily to check all is well.

We continually log all attempts to access our web sites and servers – and we check these logs carefully every day to make sure none of these attempts are potentially malicious.

Access to MasterVision itself is strictly controlled through the use of approved IP addresses, which we maintain and control on behalf of our clients – like all the best establishments, if you’re not on the list, you can’t get in.

Keeping things running

The status of our web servers is checked automatically every few minutes, 24 hours a day, to make sure they are up and running to our satisfaction, and another part of our daily routine is to monitor the reports produced by this process. In the event of a suspected issue with any of the servers, an SMS message is also sent to key technical staff, which means they’ll be alerted even if it’s out of hours.

All of these measures ensure we maintain our impressive 100% uptime record since MasterVision first launched.

Always up to date

Each of our clients’ MasterVision products is updated on a weekly basis, so the data is as relevant and up to date as it can be.

When a client’s weekly update (or ‘build’, as it is known) takes place, we carefully check all the log files and reports generated by the build process, and if necessary raise and resolve any queries with the client before making the latest version available on their live site. Of course, if there are no queries, the new build will be fully checked and ready to use often before the client’s working day begins.

Product developments and testing

We welcome change, and can react very quickly to requests made by clients for improvements to their MasterVision product – whether it’s a simple enhancement to their user interface, a handy new product feature, or the addition of a whole new data source to enrich their customer view.

If additional data sources are required, we check the new files and produce detailed reports on their structure, content and quality before we begin to process them; this helps avoid any unexpected hiccups further down the line, and keeps everything on schedule.

Each client site is mirrored to an identical test environment, where we implement and test any modifications ready for the client to assess and approve, before the changes are promoted to the live site. This means that no change, however complex, need interrupt the smooth running of MasterVision.

Through a combination of careful monitoring, attention to detail and good old-fashioned hard work, from here in the boiler room we intend to keep things that way.

By DataSalon | Posted in Technology Topics | Comments (0)

UKSG Annual Conference

April 24, 2013 – 1:08 pm

We recently attended the UKSG Annual Conference which was held in the not-so-sunny seaside location of Bournemouth. As usual the conference was well attended and packed full of stimulating talks and thought provoking breakout sessions.

UKSG did an excellent job in posting the session slides on slideshare, and even videos of some of the talks on YouTube. We enjoyed Phil Nicolson from Ringgold on data governance for publishers (a topic dear to our hearts):

Laurel L Haak gave an update on ORCID, something we’re keeping a close eye on:

And one session that we missed in person, but thoroughly enjoyed catching up with on YouTube was Jason Scott from the Archive Team proving that the best presentations don’t contain any bullet points:

As well as all the serious business, one abiding memory of the conference will be of seeing our publisher and library friends grinning like eight-year-olds whilst going round and round on the bumper cars which were laid on as part of a funfair alongside the conference dinner. Even Bournemouth council got into the spirit of the conference and were kind enough to put up a huge billboard for our product MasterVision right outside the conference centre.

Bournemouth master vision billboard

By Colin Meddings | Posted in Data Integration & Cleansing, Technology Topics | Comments (1)

Introducing our new Client Director

March 27, 2013 – 9:18 am

Colin MeddingsWe’re very pleased to welcome Colin Meddings to the DataSalon team, who joined us this month as Client Director. Most recently Colin worked in institutional marketing at Oxford University Press, and over the years he has held a variety of marketing roles within academic publishing. We’ve asked him to introduce himself by sharing a few of his own tips and insights about managing customer relationships.

A close relationship with customers

In my role as Client Director I’m tasked with maintaining a close relationship with our clients. Here at DataSalon we have a growing list of clients and make it a core value of our business to offer excellent customer service and keep in touch with them via regular communications and meetings. The nature of our business means we can offer the personal touch to every client.

This isn’t always the case for a company with a higher volume of customers such as, for example, a publisher with thousands of library subscribers. In previous roles I’ve been in exactly this position, and I can share some tips I’ve found useful, for publishers to stay close to their library customers:

  • Find out some overview customer data such as who are the top 50 customers by value, or what is the overall value of your business by region. This helps you to see the big picture and can focus your efforts on where it will have most impact.
  • Whilst the big picture is important, you also need to understand your customers on a human level, and nothing can achieve that as well as meeting them in person. Take any opportunity to meet your customers. Maybe tag along on sales visits, develop a user group, and be sure to attend industry events.
  • Extend the above principle of understanding your customers beyond just the sales team. Often it is back office or customer services staff that will be dealing directly with customers. Ensuring that all staff have the knowledge to not just do their job, but to empathise with the customers’ requirements, will result in a better for experience for all.
  • Just because you are a large scale company that doesn’t mean that your communications and marketing with customers can’t be personalised. Use the information you know about individuals to customise and target messages effectively (see our previous blog post on Why targeted marketing matters).

Keeping up with industry developments

Another side to my role here at DataSalon is to oversee our relationship with the wider scholarly publishing industry. All of the staff here have experience of the publishing industry, although in different functions ranging from technical to marketing. We like to know what’s going on in publishing as it will impact on both our own business and that of our customers. Here are my tips for keeping up with what’s going on in our industry:

  • Subscribe to industry email newsletters. Someone out there will be going to the trouble of aggregating lots of news so you may as well take advantage of it.
  • Read at least two or three relevant industry blogs. I’ve found an RSS reader to be a great tool to allow you to check in regularly and see what’s new on several blogs in one place.
  • Twitter can be a great source of industry news. You don’t have to be active yourself on Twitter. Following the right contacts can result in a customised stream of news, discussion, and gossip that can be highly informative and is often faster off the mark than more traditional news sources.
  • You can’t beat attending an industry conference or seminar for an intense dose of the latest hot topics and developments. We’ll be at the UKSG annual conference coming up in April and making the most of our time attending the sessions and meeting with our clients.

I’m really looking forward to getting to grips with my new role, putting into practice some of my own advice as well as learning some new skills.

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

A beginner’s guide to data governance

February 28, 2013 – 11:56 am

As we saw in last month’s article (“Why data quality matters”), the issue of data quality is becoming an essential point of basic good practice for all scholarly publishers. So, having noted the pitfalls of bad data and the benefits of good data, what practical steps can you take to improve things?

This is where the emerging business practice of ‘data governance’ comes into play. There’s a very good Wikipedia article about data governance, but in short it can be defined as “a set of processes that ensures that important data assets are formally managed … and that data can be trusted”. From a publisher’s perspective, the basic steps to put in place a data governance programme can be summed up as follows:

Data Quality Process

1. Plan & Prioritise. This is an essential first step in order to agree objectives, allocate resources, and gain management buy-in for the importance of good quality data as a business asset. Also, not all data is equal! So, it’s very important to assess how data is actually used, and from there to identify the most important data elements to audit and clean. For example, you’ll probably decide that Name, Address and Email details are a very high priority.

2. Audit & Analyse. The next step is to audit the quality of your existing data, which will be held in various different places (e.g. authors, subscribers, members, etc.) This allows you to profile your data and gain visibility of what’s good and bad. It will include various tests and checks, including blank vs populated fields, validation (of emails, countries, postcodes, etc.), finding outliers (unusually low or high dates and numbers), and so on.

3a. Clean Existing Data. Having identified the most important problem areas, the next challenge is to take steps to clean up your existing data. In some cases that can be automated (e.g. correcting a country of ‘London’ to ‘United Kingdom’) and in other cases that may require extra info from the customer (e.g. a missing email address), which you might plan to capture from them next time they log in (a technique known as “progressive profiling”).

3b. Improve Data Capture. The other side of data clean-up involves making improvements to the way data is entered in the first place (e.g. your online registration forms). If poor quality data is being entered, can extra checks be added at the point of data entry to prevent that happening in future? Those checks might include required fields, email validation, and so on.

4. Ongoing Monitoring. And of course, data clean-up isn’t a one-time task. Regular auditing, spot checks, and tracking reports over time will ensure that your data stays clean. Creating dashboards can be a useful way to define and track key data quality measures – to ensure that your data governance programme is having the desired effect.

If you’d like to discuss how DataSalon can help you with data quality and data governance, just contact us requesting further details.

By DataSalon | Posted in Data Integration & Cleansing, Management Essentials | Comments (0)

Why data quality matters

January 31, 2013 – 11:27 am

Binary Code“Only four types of organisations need to worry about data quality: Those that care about their customers; Those that care about profit and loss; Those that care about their employees; and Those that care about their futures.” – Thomas C. Redman (2006)

Over recent years publishers have had to overcome many hurdles in the digital world, such as making content available online, managing complex consortia deals, creating new packages of content and tracking usage statistics. The result of all this digital activity is vast amounts of data. However, the pace of change can often distract from the careful governance of this data, leading to gaps, inconsistencies and inaccuracies.

But why does the quality of all this data matter so much? Good data is your most valuable asset, and bad data can seriously harm your business and credibility…

1. What have you missed? At a management level, poor data quality equates directly to poor visibility of key trends in the growth or decline of certain products or markets. At the contact level, you may miss out on valuable sales opportunities if email address fields aren’t filled out correctly or customer names are wrong. Having good data will help deliver better customer service and enhance your reputation, and it means you can make better selections for targeted prospecting, cross-selling and up-selling.

2. When things go wrong. Bad data can lead to ‘accidents’ and wrong decisions or actions which can affect customer confidence. You’ve spent time building up a valuable customer list – so it’s important not to waste this by sending campaigns to the wrong people, or with messages which don’t match their interests, or to out-of-date or deceased contacts. Data quality issues can also cost you money directly – for example if invoices or renewal notices are sent to the wrong recipient, or at the wrong time.

3. Making confident decisions. Data quality matters most of all because it enables your staff and management team to really trust the accuracy of the reports and analysis they’re given. Without that confidence, apparent trends or new opportunities will always leave you wondering whether they really present a true picture. But with a complete and accurate view of your customers and prospects, comes the confidence to make well informed business decisions and commit fully to your strategic planning.

So, data quality is a very important foundation for a publisher’s entire business planning process and customer contact strategy. Good data quality will allow your business and its reputation to grow and flourish. We’ll look at some practical steps to address data quality issues in a future article.

By DataSalon | Posted in Management Essentials | Comments (1)

Understanding the analytics iceberg

October 31, 2012 – 11:50 am

Publishers are awash with useful data about authors, customers, usage, and plenty more, and it has never been easier to grab a set of numbers, put together a few charts in Excel, and create some interesting reports.

Suppliers have been doing this kind of thing for years of course: with email marketing providers charting open rates and click throughs, web analytics tools graphing website traffic, content platforms tracking article download trends, and so on – in each case analysing the particular chunk of customer data those systems have readily available.

Individual publishing staff often do something similar in-house: manually putting together dashboards in response to management demand for headline reports, often with many long hours of effort in collating data and presenting it visually.

However, the results of all those types of efforts don’t entirely hit the spot. Presenting the numbers you have to hand with an attractive chart is just the tip of the analytics iceberg – it’s just the ‘quick win’ providing only limited insight or longevity – because a really effective analytics programme requires a whole mountain of extra work beneath the surface to create reports of lasting value which are truly comprehensive, trusted, and repeatable. Let’s briefly look at each of those 3 aims to understand why there’s so much more hard work to be done beneath the surface:

1. Comprehensive. Scholarly publishing is quite a complex business, and any single measure in isolation isn’t going to tell the full story. For customer analytics to be comprehensive, at the very least they need to synthesise the "big 3" elements of author submissions, subscription sales, and article usage. With any one of those elements missing, your analytics will have a blind spot regarding the creation, selling or consumption of content, all of which are critical health indicators for every publisher.

2. Trusted. Doubts over accuracy can often undermine the value of customer metrics, so a carefully de-duplicated single customer view is an essential foundation for any analysis – without it there’s a high risk of double counting customers. There’s also a lot of work required to ensure that revenue counts match the figures from accounts, and to properly allocate fees from complex multi-site or consortia deals. Data quality is also a major challenge when consolidating variant names and codes for different products, packages, countries and regions. If all those issues can be overcome, then you can start to create reports which people really trust.

3. Repeatable. Ensuring analytics are repeatable doesn’t just mean doing it again, it means being able re-create the same measures in exactly the same way, month in month out. Repeatability is the biggest problem with many hand-crafted in-house dashboards: it can often become too difficult or too time-consuming to reproduce those exact same reports consistently over time. And of course without consistent tracking, there’s no visibility of recent trends, and no feedback on whether steps taken are having the desired effect.

So, if ever you’ve thought that customer analytics are all about presenting numbers via charts and dashboards, then bear in mind the ‘analytics iceberg’. There’s a lot of hard and specialist work to be done beneath the surface to produce reports which will be comprehensive and reliable enough to provide real long-term insight and value.

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

The 7 deadly sins of data quality

September 27, 2012 – 9:01 am

One of the side effects of creating an integrated single customer view with a system like MasterVision is that it can bring to light issues of data quality which may previously have been hidden from view in various separate source systems. Since data quality is a tricky concept, let’s take a quick tour of the different types of problem which can arise:

1. Gaps. You’ve captured a customer’s details, but certain crucial pieces of information have been left blank. That might be their country, or their email, or even their name. This can be solved (for new sign-ups) by striking the right balance between making your registration form quick and easy, while still requiring users to fill in certain key fields. For existing customers, you can fill any gaps with ‘progressive profiling’ – ie. configuring your systems to ask the customer for a little more info next time they log in.

2. Duplicates. There’s also the challenge of tidying up multiple records for the same customer. De-duplication is difficult to get right, because the aim is to find and merge all of the duplicates, while avoiding ‘false positives’, whereby similar but different customers are wrongly merged together. The best approach will vary depending on the nature of the source data, but often involves a mixture of email, phone, name, and address info. It’s important to get this right, otherwise any analysis will overstate the number of unique customers you really have.

3. Errors. These can take many forms, but typical examples include incorrect info such as a country value of ‘London’, or plain ‘junk’ info such as a country value of ‘zzzz’. Those might be reasonably easy to find in a field like country (because there’s a finite list of correct values), but harder to find in a personal name field. And even having found incorrect and ‘junk’ values, those fields will then often need to be blanked (in the absence of any better values), so producing more ‘gaps’ to be filled.

4. Inconsistencies. A different type of issue arises where perfectly valid info has been entered inconsistently. One example might be a title entered as ‘Mr’ by one customer, ‘Mister’ by another, and ‘MR’ by a third. These all clearly mean the same thing, but the various forms will make it harder to analyse the data cleanly. This same issue often arises for product info too, where different codes and names are used in different systems, even when referring to exactly the same product. With the right tools, inconsistencies like these can usually be cleaned up very effectively.

5. Missed connections. When dealing with hierarchical customer data, missed connections can arise where an individual isn’t linked up to their parent organisation. This will then reduce the quality of the organisation’s profile, since the activities of all related individuals won’t be taken into account. If referencing a third-party market database (such as Ringgold), then similar quality issues will also arise if your organisational customers are not correctly linked. Both of these problems can be fixed either with manual auditing or with automated linking tools.

6. Old information. A more subtle data quality problem can arise if you have old data about a given customer. Their key information may all be present, but if it was provided many years ago, then there is a much higher risk that it is no longer accurate. Almost every piece of info you might hold about a customer can change over time, including their address, email, phone number, interests, and even their name. Customers may also have died, and marketing to them in those circumstances can be very distressing for relatives. For all these reasons, trying to keep your customer info reasonably up-to-date adds another dimension to the data quality challenge.

7. Conflicts. The seventh and final deadly sin of data quality relates to conflicts. What to do if the same customer has opted in to marketing in one of your databases, and opted out from all contact in another? And if you have more than one postal address for a customer, which one do you choose for your next mailing? And if you have more than one email address, which is the right one to use? These types of conflicts are a natural part of creating a single customer view. They can all be resolved by putting in place the right business rules to choose the ‘best’ option in each case – which might be based on the most recent record, or on treating one source database as ‘more trusted’ than others, or some other criteria.

So, in conclusion, data quality can present a lot of different headaches, but all of these areas do need to be tackled with care, in order to create a reliable and accurate overview of your whole business which you can really trust.

By DataSalon | Posted in Data Integration & Cleansing | Comments (0)

Why all projects are a bit like the Olympics

August 30, 2012 – 8:55 am

London 2012With the Olympic torch now extinguished and the Paralympics just underway, we’ve been reflecting on what we could learn from this summer’s London games. Although the multi-million pound budget and worldwide scope were on a somewhat larger scale than those of your typical business or IT project, we did note some points of comparison, and maybe even some useful lessons…

1. Planning. It took a huge amount of preparation to make the Olympics a success. Before even the first scoop of earth had been turned at the Olympic park, thousands of hours had been put into researching and writing a detailed plan. Whilst an internal project is unlikely to be seven years in the making, it equally shouldn’t commence without proper planning – rushing straight in without due thought can cause major headaches further down the line.

2. Detail. When working on a project it can be very easy to focus so much on the big picture that you forget the importance of smaller details. However, attention to detail can be key to a project’s success, and overlooking this can cause significant problems, as seen at the Olympics when images of the North Korean women’s football team were shown alongside the South Korean flag.

3. Hard work. Delivering the London Olympics took a lot of hard work ‘behind the scenes’, with what we all saw representing only the tip of the iceberg. This is also true of business projects: when looking at the final result many people are unaware of just how much hard work it has been to reach the finishing line. Just as medal winning athletes endure unglamorous hours of training away from the spotlight, projects often owe their success to long hours of hard work from key staff at evenings and weekends.

4. Persistence. Your project, and your attempt to solve a business problem, might not succeed first time but that doesn’t mean that you should give up. Rower Katherine Grainger won 3 silver medals at 3 consecutive Olympic Games before winning her gold at London 2012. Then again, sometimes a change of direction is the best course of action, as demonstrated by the numerous cycling medal winners who started off their sporting careers in rowing. If despite careful planning and lots of hard work your project is still not getting results, it might be time for a tactical change of focus.

5. Goodwill. London 2012 has been widely seen as a success but it wasn’t perfect, with some empty seats despite massive demand for tickets, Olympic lanes causing traffic chaos, and some athletes stripped of their medals for doping offences. However, these were all eclipsed by the public’s goodwill and enthusiasm: from the torch relays to the Olympic ‘Games Makers’, much was done to make everyone feel positive about the event. Similarly, no business project will ever be perfect and problems should be expected, but these inevitable blips will be forgiven if you work hard to keep all the key stakeholders and end users on-side.

By DataSalon | Posted in Technology Topics | Comments (0)

Why targeted marketing matters

July 26, 2012 – 1:31 pm

In our time of email marketing it’s relatively cheap to send a mass message to all of your contacts, and it’s also easier to create a campaign like that, since there’s no effort required to select the most relevant contact list. While this can be valid in some contexts (eg. to a niche list, or to announce an amazing “Everything must go!” discount offer), in general we think it’s much better to tightly target your marketing campaigns, for a whole variety of reasons.

Better engagement. Even with a general message such as “Sale now on!”, you can engage with your customers by applying a hook that will speak to them personally. Let’s say you mainly buy children’s clothes from an online clothing company. A “Sale now on!” email would be welcome, but a more targeted message of “Sale now on! Big discounts on kids’ clothes” is much more likely to engage and interest you, and so much more likely to earn a click-through.

Lower ‘unsubscribe’ rates. Sticking to the same example, an irrelevant promotion for products you never buy, such as “Big discounts on men’s footwear” is probably going to to wear out your inbox goodwill and have you reaching for the ‘unsubscribe’ button. This is a crucial point, because once you’ve unsubscribed, then you’re ‘lost’ to the retailer for all future email marketing. That’s one of the reasons why targeting is so important: it’s essential to the long-term health of the list.

Good for marketing morale. From the point of view of your marketing team, if you send out a ‘broadcast’ email to your whole database, it will probably only be relevant to some recipients, and so might produce disappointing response rates. It’s important to remember how bad that can be for morale within the marketing team, who naturally wish to feel like effective marketeers rather than corporate spammers. On the flip side, a carefully planned and well-targeted campaign will show a much higher response rate – effectively a group ‘thumbs up’ from your customers, and a big feel-good factor for the marketing team who can take pride in a job well done.

Good for your brand. All of these points together add up to a boost for your brand. Customers are people, and people like to feel important, appreciated, and valued. A well targeted message can convey all of this back to the customer, and reassure them that you value their business. If that’s done well enough, you may even start to get a “word of mouth” effect, whereby happy customers may mention your excellent service and relevant emails to friends. Conversely, it’s easy to imagine a customer bad-mouthing your company for bombarding them with irrelevant offers.

The bottom line. While there’s clearly additional up-front cost in obtaining the right tools to support highly targeted segmentation, your sending costs will be lower when targeting smaller groups (and those savings can become very significant if sending printed materials in the mail). And beyond lower sending costs, the financial benefits from happy and engaged customers and low ‘unsubscribe’ rates in the longer term can also be substantial – both directly via new sales, and indirectly via brand benefits.

So in conclusion, targeted marketing isn’t just about keeping down sending costs, there are a whole range of benefits for the customer and for your staff. If your marketing team don’t yet have an easy way to define and select highly targeted lists, it may be time to start thinking about giving them that support.

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

How engaged are your customers?

June 27, 2012 – 8:56 am

A key first step to a better understanding of your customer relationships and to tailoring your communications to contacts is to bring all of your customer data together into a single view. This is a good starting point but it’s not necessarily ‘actionable insight’. What might be really useful here are comparative measures ‘sat on top’ of the raw data. You could then use these to inform how you interact with different customers to get the best outcomes for your business.

Engagement profiling is a technique that identifies different areas of activity/interaction and assigns a relative score to each customer, ranking them on a scale from 100 (top) to 0 (bottom). These scores can be both overall for each metric you’re interested in as well as per product. A total engagement score, combining all measures together with weighted percentages, can also be inferred for a high level overview.

What activities/interactions might you consider for engagement scoring?

1. Subscription Spend. Knowing how much a customer spends on your products is a very significant piece of data. Ranking customers by their ‘active’ spend and perhaps also their ‘lapsed’ spend for each product and overall is a must-have measure of their engagement with you.

2. Usage. The number of full text downloads this year/last year is one thing but do you know how a customer’s usage compares to others and how it varies across different products? Is the trend going up or down? What might be causing high engagement on spend but dipping usage? Spend and Usage engagement metrics – when taken together – give you a great means to identify both ‘safe’ and ‘at risk’ revenues.

3. Individual Contacts. Another good indicator of engagement is how many related individual contacts you have at each institution. If you are inferring these connections via email domain and institution name matching techniques then assigning a relative score to each institution for their total number of contacts is just one step away. You could score at more granular levels too, e.g. ranking institutions by the number of newsletter/alert recipients.

4. Pay-Per-View Spend. Linking pay-per-view transactions made by individuals to their related institutions and then ranking those institutions by that total spend figure can provide a good indication of the level of interest in and demand for your content.

5. Authors & Reviewers. Linking manuscript submissions/review activity by individuals to their related institutions and then ranking those institutions by that activity is a similar idea but a different perspective on your customers’ engagement with you.

These are just a few examples and we’ve focused on institutions here but the same technique can be applied equally well to your individual customers too. With relative scores for each customer along a number of important dimensions, plus an overall engagement metric, you are taking your single view to a new level with valuable additional insight. It’s then an easy next step to use this to better segment your customers and drive communications that can help address risks and achieve growth for your business.

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