Idiro researcher holds seminar on Social Network Analysis in telecommunications

Academic research has always been important to Idiro – that’s how we became world leaders in the application of Social Network Analysis (SNA) techniques to telecommunications business problems.  It is also why our CEO is on the board of CeADAR, the Irish Centre for Applied Data Analytics Research.

So we are happy to report that our colleague Davide Cellai, who has been working on advanced uses of SNA in solving telecommunications business problems, this week gave a seminar at the University of Aalto, Finland on his advanced SNA churn research.  Davide says:

“Last Thursday I was invited to give a seminar at the University of Aalto, near Helsinki. This week, I have been hosted by the group of Jari Saramaki and Kimmo Kaski, who were possibly the first researchers to focus a research group in social network analysis applied to telecommunications, several years ago. I presented our work on port-out churn, plus some percolation models of robustness of infrastructures I have been involved with in recent years.  Here are some examples:

Social Network Analysis in telecommunications - research by Idiro Analytics
Distribution of fraction of time two subscribers spend speaking to each others in an interval of 12 weeks

In order to profile the type of connection between pairs of subscribers, we calculate the amount of time two individuals spend at peak (i.e. during working hours) and off-peak time of the day. For each pair, we can evaluate if conversations occur mainly at peak or off-peak time and give a score accordingly. In the first figure, we show the distribution of this score over all the phone calls that occurred in a period of 12 weeks. We can see two strong peaks, representing calls occurring exclusively off-peak and at peak times, respectively. We also show an enlargement of the central zone, with a broad hill representing pairs of subscribers who speak both at peak and off-peak time. This polarization suggested us to identify three layers of acquaintances: peak, off-peak, and mixed peak/off-peak.

Social Network Analysis in telecommunications - research by Idiro Analytics
Probability that a subscriber churns as a function of churning subscribers in her network of social acquaintances
This plot shows the probability that a subscriber churns after m_out of her friends have churned in a recent time interval. Generally speaking, we can see that a subscriber with more churning friends is more likely to churn, as the red crosses tend to grow with m_out. Moreover, we can see that the probability of churning is higher for the mixed peak/off-peak layer (purple boxes), meaning that at this level of relationships, churning propagates more easily.
The seminar participants were quite interested in the way we could identify types of social acquaintance based on the time of calls. They also suggested that exposure to churn in terms of duration, instead of number of churners, would improve the sensitivity of the method. In particular, Jari Saramaki, who has also experience in the data analytics industry, envisions that machine learning methods should be fed with this kind of insightful social network information to produce best lift.

The week I have spent here has been very useful. For example, researchers have shown me a method to identify families that doesn’t use any community finding algorithm, and a way to map a temporal network into a network of events, that can be treated with a known formalism. Another post-doc is working with psychiatrists to detect the onset of a mental disorder in the pattern of social activities of a person. Finally, it has been also interesting to hear that a few students or post-docs are starting a company. Best of luck, and thank you Aalto!”

Idiro gratefully acknowledges the support of Science Foundation Ireland in this work.  Idiro works with telecommunications companies across the world, helping them with customer retention, customer acquisition etc.  To learn more about Idiro’s work on Social Network Analysis in telecommunications, or to find out how Idiro helps telcos to get better marketing results through our SNA models, contact our experts.

Renaming to Idiro Analytics – A letter from the CEO

Idiro Analytics Logo Jan 2015

Dear customers,

We have just renamed our company from Idiro Technologies to Idiro Analytics. It is a minor change but we felt it was important to do as it more accurately reflects the service that we have been delivering to our customers since our inception.

While we continue to innovate and develop new technology our customers are primarily focused on the benefits we deliver rather than on the underlying technology used to deliver those benefits. As such, we felt that changing the company name to Idiro Analytics would communicate the nature of our business in a more precise manner.

On behalf of everyone here in Idiro Analytics I’d like to take this opportunity to thank you for your continued support.

Yours sincerely,

Aidan Connolly, CEO

People and data; a truly symbiotic relationship

141201.unbiased

We need data and it needs us. Every day, businesses are using data to learn more about their customers, better-target their marketing campaigns and increase their ROI. The right data can do a lot for your business, but without the right people to analyse, interpret and utilise it, your business goals can suffer.

A problem users of data face sometimes is that they are guilty of ‘cherry-picking’ the data they need to support ideas and opinions that they already have. As put in this article by Tom Fishburne: “Data doesn’t have biases. It’s people who collect and select the data who bring bias to it.”

It’s imperative to your business goals that you and your business are using your data as effectively and efficiently as possible. Here at Idiro, we not only have the skills to turn your data into actionable insights but we also have the perfect people to help you use your data to it’s highest potential.

We’ve placed SNA consultants in companies with excellent results. To learn more about our SNA Consulting services, please contact us at: experts@idiro.com

Latest WOMMA study showcases power of Word-Of-Mouth marketing

A recent study by the Word of Mouth Marketing Association has produced some interesting and insightful figures relating to the power of Word Of Mouth marketing. The study focused on offline WOM conversations as well as social media. Some of the key points that resulted from the study are as follows:

– WOM drives 13% of consumer sales in the US, which amounts to $6 trillion annually
– WOM boosts effect of paid media by 15%
– Offline WOM accounts for two thirds of sales impact, with online social media accounting for one third
– An offline WOM impression drives 5 times the sales impact of paid media alone, and up to 100 times for higher-consideration categories
– WOM’s impact happens close to time of purchase, often within two weeks

Word Of Mouth Infographic

Even though we know that consumer recommendation has a powerful impact on sales, it has been hard to quantify thus far, with much of offline WOM data difficult or impossible to record. Bearing the above figures in mind only further emphasises the need to target marketing campaigns at influencers, i.e. those who are most likely to drive WOM marketing and amplify your paid media efforts.

Idiro’s award-winning SNA Plus predictive analytics platform can help you identify influencers  within your customer base enabling you to better-target your campaigns and increase your ROI. For more information, please visit our Case Studies page, or contact us at: experts@idiro.com

Measuring ROI Of WOM Marketing

AT&T’s Greg Pharo recently joined Ed Keller of the Keller Fay Group for a webinar on the Return-On-Investment of Word-Of-Mouth (WOM) marketing. He shared insightful information on AT&T’s research into WOM and the significant role it plays in driving new customer acquisition.

Keller stated at the beginning of the webinar that in a recent study, approximately 85% of marketers in the US couldn’t show the ROI of WOM marketing, despite plans to increase their budget spend in the category. A McKinsey article also noted WOM as being the most ‘disruptive’ marketing factor, adding that WOM is responsible for 2.1 billion daily brand impressions in the US and 440 million in the UK.

One particularly interesting statistic was that of the 90% of WOM marketing that happens offline (which is interesting in itself), over half of this was driven by one or another form of marketing or media. Of particular importance is the fact that 26% was driven by paid advertising. Targeted advertising is obviously a vital factor in driving sales through WOM and on the back of that, identifying who to target remains an increasingly important challenge. Being specialists in advanced and predictive analytics, Idiro can identify propitious customer segments so that marketers can better target their campaigns, in order to capitalise on these new figures emerging from AT&T’s research.

Although paid media remains the primary driver of sales for AT&T at 30%, WOM is a close second. Pharo elaborated on this by saying that WOM explained over 10% of sales through positive comments, but also over 10% of lost sales through negative comments.

ROI Of WOM

He concluded his thought-provoking presentation by saying that WOM metrics belonged on a CMO dashboard as a KPI and that WOM is ‘an impactful, relevant variable for influencing sales in the Wireless industry’. He believes that conversation should be a marketing objective for all marketers and Ed Keller went on to explain the best ways for those marketers to stimulate WOM:

1. Focus on ‘talk-worthy’ messages, i.e. ‘triggers’

2. Target consumers who can carry messages, i.e. ‘influencers’

3. Favour marketing/media that maximises WOM, i.e. paid advertising

He also added an interesting point at the end that maybe all media should be thought of as ‘social’.

Idiro’s expertise in predictive analytics can provide marketers with a thorough analysis of their target audience, identifying the key influencers amongst communities and even amongst families and households. Using the SNA Plus platform, marketers can really take full advantage of the power of WOM, which, if this webinar is anything to go by, will remain a key sales driver for years to come.

How women influence each other’s purchases

My wife has just bought a new car.  We made a shortlist and test-drove three, but the early front-runner was the one that her friend Bernie drives and recommended.  And so it came to pass that that she bought the same car as Bernie has. It’s a great car incidentally – but without Bernie’s recommendation, it is unlikely that my wife would have considered it.

I thought of Bernie when I read an Adweek article about a survey carried out by the USA-based ‘Ladies’ Home Journal‘ on the ways in which women influence others’ purchases.  Adweek published an interesting infographic on the survey.

Ladies' Home Journal survey - how women influence each other
Ladies’ Home Journal survey – how women influence each other

The importance of peer influence to decision-making come as no surprise – these are broadly in line with Idiro’s own empirical research and with most published studies, including Nielsen’s annual survey on trust in advertising.  Interestingly,t he list of purchases that are most influenced by peers includes low-priced and much higher-priced items – note that automobiles come in at #4.

More controversial is the finding that ‘peer influence is age-agnostic’.  Most studies agree that closeness of age is a driver of peer influence – the closer the parties are in age, the more likely they are to influence each other, which makes sense.  Idiro’s own empirical research finds that similarity of age is a significant determinant of influence.  However, unlike Idiro’s research, this survey measures perceived influence not the actual purchases, which may account for the difference.

Though this survey is USA-based, Idiro’s experience (and the latest Nielsen global advertising survey) suggests that results would be broadly similar in other countries.  It would be interesting to replicate this survey among men – doubtless the detailed results would be different, though the level of influence would be doubtless be fairly strong.

To learn more about how Idiro can help with influencer marketing, check out our case studies or contact us.

Postscript 16th May: this research from Nielsen India breaks down the stated influence on car purchase between spouse, family members, friends and colleagues (see graphic below).

Influences on Indian car buyers. Source: Nielsen

How to run a successful trial of Social Network Analysis for marketing

At this stage, everyone in marketing understands the power of word-of-mouth – which Tom Fishburne’s cartoon, below, elegantly illustrates. Organisations with link data – telcos, gaming companies, social networks and the like – can take a scientific approach to word-of-mouth marketing (aka influencer marketing) by deploying Social Network Analysis algorithms to target the influencers – or the influenced.   Idiro is a pioneer in this space.

Over the past few weeks we have been talking with two mobile operators who, prior to talking to Idiro, had each run projects to evaluate the benefit of Social Network Analysis (SNA) for improving targeting in marketing.  However, in both cases the trials ran into difficulties that could have been avoided. At the end of the projects both mobile operators had invested significant time and money in running a trial, but neither was in a position to make an investment decision.

We’ve been involved in mobile operator trials of Social Network Analysis for over eight years, and we’ve seen the good, the bad and the downright ugly – so we know how to run a successful trial of Social Network Analysis for marketing. Here are eight tips to help you run SNA trials that give you a clear evaluation of SNA for your business – quickly and efficiently.

1. First, be really clear on your objectives

It might sound obvious – but are you proving a technology, evaluating a vendor or trying to find the best way solve a business problem? Be really clear on this, both internally and with your SNA trial vendor(s). Also, how serious is your organisation about adopting a SNA solution if the trial succeeds?  We evaluate operators who come to us looking for SNA trials on 2 axes:

  • To what extent are the key sponsors prepared to accept the concept behind SNA for marketing?
  • The degree of organisational backing / commitment to deploying a SNA solution if it is proven (worst case: a solo run, best case: a project with board backing)

Make sure your organisation is prepared to invest in a solution before you start your evaluation of SNA.

2. Work out the evaluation, decision and implementation steps in advance

A common cause of trials not completing successfully is that the assessment of SNA that they deliver is not what the senior team needs in order to make the investment decision.  Therefore, before you finalise the trial, work out the evaluation process and success criteria. We offer our customers help with evaluation methodologies for SNA in marketing.

3. Design the trial carefully based on your objectives and your approval process

Many mobile operators make the mistake of specifying too much technical detail (while leaving the business success criteria too loose).  Others base their trial design on the offering from a particular vendor. We all know which vendor will perform best in a trial like that!

Different SNA solution vendors have different philosophies, and it is usually best not to specify the vendor’s methodology or business model tightly, at least initially, and focus on the business benefits that are required (see point 1). That way, a wide range of vendor approaches can be tested – and ideas that you did not think of can be incorporated into your project. Use the agreed evaluation method and success criteria to inform the key elements of the scope:

a) Live or historical trial, or both? b) Role and design of control groups c) Technical  / operational models to be considered (Saas, managed service, software licence, etc.)

These are important choices, and they will affect the outcome of your trial.

4. The farmer and the cowman should be friends

The most successful SNA implementations tend to have close cooperation between marketing and analytics teams. Whichever side of the organisation you work on, bring your colleagues on board early.

5. Get the trial campaign right

Because they target the influencers or the influenced in your customer base, word-of-mouth campaigns need to be designed carefully. If your evaluation involves a campaign, don’t put all your effort into the technology and test it on a bog standard campaign.  Idiro are experts in word-of-mouth campaigns.

6. Budget

Be realistic about how the relationship between spend and quality. Most vendors want to cover their costs at least, during the trial. You could doubtless persuade one or two vendors to work for free, but this might mean that you exclude the best vendors. Remember also to budget for internal costs.

7. Fix a realistic timescale

SNA trials with thorough methodologies take time to do properly. Trials with highly aggressive deadlines nearly always overrun – typically because one or more internal tasks do not receive the priority they need. Set realistic deadlines and make sure your internal project manager has the authority to get the tasks done.  Beware of shortcuts, particularly around evaluations.

8. A successful introduction of new technology requires change in the organisation, which isn’t easy

A successful post-trial implementation leading to a strong ongoing ROI depends on getting a number of factors right – operational, analytical, process change, KPIs, etc.  When post-trial implementations fail, they do so because they don’t address these difficult issues or don’t have a strong leader keeping the focus on the benefits.  Once the SNA trial is completed, the benefits are proven and the contract is signed, make sure you task the team with delivering the benefits within (say) 6 months and not just completing the implementation project.

 

Idiro would be happy to expand on any of these points.  If you are planning a trial of Social Network Analysis solutions for marketing, feel free to run your ideas by us. We might save you some heartache.

The Customer Effort Score and contagious complaining

In the never-ending quest to find new ways to measure a company’s success with its customers (and to earn fees for the consultants that promote them), the Customer Effort Score has become one of the more fashionable tools.

What is the Customer Effort Score?

For some years, companies have been exhorted to delight their customers – the idea being that delighted customers become loyal and tell their friends how good the service / product is.  This approach has given us the popular and fashionable Net Promoter Score, for example.

The idea behind the Customer Effort Score is that most customers of most companies won’t be delighted if they receive great service – and that therefore a company should instead focus on avoiding bad service.  The Customer Effort Score is a measure of how much effort a customer has to make in order to get a problem fixed.  We have all had problems with suppliers that take up huge amount of our time to get fixed, and the idea is that if a company can just minimise the difficulty of getting problems fixed, that will strike the right balance between customer dissatisfaction and funds invested in customer happiness.

That seems to make sense – especially, dare I say it, for corporate behemoths that never had a hope in hell of delighting more than a select few anyway.  And it particularly makes sense for those products that consumers largely consider as hygiene factors in their lives (i.e. the consumer only notices them by their absence or non-performance).

BT’s ‘Net easy’ implementation of the Customer Effort Score BT have been using the Customer Effort Score (CES) for some time, and find it useful for evaluating channels – but only when taken with other measures such as the Net Promoter Score.  Calculation of the score is fairly simple, as the graphic shows – however BT and others underscore the importance of asking the questions in the right way.  CEB tested a number of question variants and found the difference to be striking, as one would imagine.  Remember that CES only measures effectiveness of customer care – if the car you bought drives like a sack of spuds or poor infrastructure means your broadband is slow, good customer care processes won’t fix the problem.

Complaining is contagious

A huge part of the value of delighted customers – and the cost of unhappy punters – is in the fact that we tell our friends about our experiences.  So which has the bigger economic effect – sharing horror stories or evangelising?

mind of consumer

We know that when a person feels passionately positive about something, she is likely to share the information with her friends.  From the success of Paul the Apostle (a fine word-of-mouth marketer if ever there was one) in spreading the Christian message to Idiro’s awards for driving uptake of iPhones, we know that passion drives commitment.  However the big issue for companies is that most companies have very few passionate fans.  For most products, the number of evangelists is tiny or zero.  Mr. Fishburne‘s cartoon, above, paints it well.

For every 100 who complain, another 170 friends will also complain
Friends of complainers are much more likely to complain themselves

However, complaining is much more common – and it certainly is contagious.  Research conducted by Idiro has shown that people who complain about their mobile phone operator are highly likely to associate with other complainers – or to encourage their friends to complain also.  In fact, Idiro found that friends of complainers are 70% more likely to complain themselves than are the rest of the customer base.  Backing this up are others’ research findings that customers are more likely to share negative stories than positive one (examples here and here).

Conclusions

Because complaining is so viral, and because typically there is a lot more customer dissatisfaction than evangelism in the customer base, then the Customer Effort Score is a worthwhile measure – particularly where customer service interactions represent a significant part of the customer’s product / service experience.

However, the CES only measures the quality of problem resolution / customer service interactions.   Clearly, other measures must be used to assess the rest of the customer proposition against customer expectations and competitive offerings.  And one useful empirical way to research both the complainers and the evangelists is to measure the word-of-mouth about your product: who is talking, about which product, what are they saying, and where are they saying it?  And if your business has data on your customers’ social links, Idiro can help you turn it into marketing insights.

Insights from the IQPC number portability summit

Freddie McBride of CEPT presenting on service portability

I had the privilege of attending the IQPC Number Portability Global Summit earlier this month.

Number portability has been important for the development of competition in telecoms.  The conference addressed a wide variety of topics around the subject.

Here are some of the points that resonated:

  • According to one speaker, 75 countries have implemented number portability (NP) on their fixed (FNP) or mobile (MNP) networks.
  • Many others, including Jamaica, Trinidad, Afghanistan, Armenia, Togo and Tunisia are likely to implement number portability by the end of 2014.
  • Some countries, e.g. Russia, are struggling against technical and political barriers to implementing number portability
  • User experiences of MNP vary widely.  In Portugal, callers to ported numbers are greeted with a message warning them that the call may cost more.  In countries like Ireland, Ghana and Israel, mobile numbers can be ported in under an hour, whereas in some other countries it can take weeks.
  • In some countries (e.g. UK) the customer approaches her current network and requests porting (this is known as donor-led porting).  Best practice, followed by many countries, is that the customer requests porting from the network to which they wish to port (recipient-led porting).
  • The technical platforms and processes underpinning porting continue to evolve, in response to customer needs (or rather operators’ new product opportunities), technical advances and the pursuit of efficiencies.

My talk to the conference covered three areas:

1. The evolution of in the importance of number porting

Mobile numbers will continue to be an important way to be reached by almost all mobile users, but callers can now find and contact at least some of their targets on social media.

Porting
The evolution of the importance of number portability

Against that, the cost and difficulty of porting is now very low in most markets, so porting will continue to be popular for the foreseeable future.When truly portable mobile phones arrived (first for businesses, then with the advent of prepaid, for the mass market), the mobile phone number filled a need left unfulfilled: a simple reliable means of reaching someone anywhere, anytime.  Porting was introduced to improve the free functioning of telecoms markets.  In 2003, the value of porting to the Irish economy was estimated at £IR 129M.

More recently, social media has emerged as a far superior way to find and contact people.  Although it has limitations, it removes many of the costs of changing the mobile number.  However, in parallel the costs (monetary and service interruption) to users of porting continue to decline, and many operators incentivise port-in.  Number porting is here to stay.

2. Insights based on analysing data around porters.

Idiro has analysed data relating to porting customers in a variety of markets.  I presented a number of insights (anonymised, of course) on the characteristics of porters based on multiple markets.  I also described in detail the phenomenon of porting contagion.  The power of word-of-mouth results in many consumers following their friends when they switch networks.  This accounts for a high proportion of porting overall.  Big thanks to my colleague Lorcan Treanor for the analysis behind these insights.  Please contact Idiro to learn more about these insights.

3. How Idiro SNA helps meet the challenges of porting churn

Idiro SNA is a perfect fit for the marketing problems around mobile number porting.  Idiro scores can be used:

Porting campaign
Success of member-get member porting acquisition campaign using Idiro SNA scores
  • In Member-get-member acquisition campaigns.  Idiro identifies the customers on competitor networks who share communities with phone users on the operator’s own network.  The likelihood of these to port in is measured.  For the most promising targets, the on-net friends are identified for targeting with a member-get-member campaign.  This can provide very strong results.
  • In retention campaigns to reduce porting churn. This Idiro score is particularly popular with Idiro’s customers.  Idiro runs weekly or monthly models to predict porting churn, and Idiro’s customers use these scores in automated weekly or monthly retention campaigns, as well as in other areas such as the call centre.

I was conference chairman on the second day of the conference, which focussed on Service Portability.  There is great interest in the topic – where the customer can port not only their fixed and mobile numbers but other elements of their package as well, up to the entire quad-play bundle.

Though the concept is an appealing one, in practice the challenges are large.  Imagine being a customer with a home phone, mobile phone, TV and broadband bundle, and moving it to a competitor.  Every provider’s service bundle is different, and porting the entire bundle will require the customer (or the recipient operator) to make careful choices.  In addition, speakers pointed out that the delay in porting different services will vary, so during a transition period the customer will have some services from the door operator and some from the recipient operator.

There are challenges aplenty there and it is clear that there is no consensus over the best way forward.  One might (at the risk of overestimating the similarities) say that the discussion on service portability is where the number portability was 25 years ago.

Overall, the conference was well-organised and the  speakers well chosen.  However, like with many other telecoms conferences, the voice of the customer was hardly heard at all.  Quality was mostly described  in narrow telecoms terms, rather than the quality as measured by the user.  Almost no primary or secondary research on customer experience was presented by regulators, operators or vendors.  At the end of the conference (I missed one talk) I had not learned anything about consumers’ expectations for porting and how well they were being met.

If the voice of the consumer is not heard, how will their needs be met?  It was ever thus in the telecoms industry – or at least, it has been for the last 25 years – and it is reason that OTT services like Whatsapp are eating SMS and MMS’s lunch.  Despite being excellent in what it did cover, by its omissions this conference reminded me again of why the telecoms industry needs to cop itself on and develop a passion for the customer, or risk its share of customer communications being progressively eroded.

Sex, teenagers and Big Data

A good friend said to me recently that Big Data and analytics is a bit like teenagers and sex; everybody is talking about it but very few are actually doing it. I think he may need to update his knowledge of teenage behaviour but I got his point nonetheless.

 

The rush to Big Data has the usual hallmarks of other past industry hot trends i.e. lots of hot air and hype. Additionally, there are a lot of definitions of what Big Data actually is and what differentiates it from, say, your bog standard Oracle BI/data warehouse.

So what’s my definition of Big Data? If pushed I’d say something similar to the following: “Big Data is the discipline of analysing vast volumes of structured and/or unstructured data with a view to generating insights and predictions that improve business performance”  (OK, I know that’s not very inclusive of non-business activity but you get the general idea).

My gripe about some soi-disant Big Data companies is that all they have done is moved their dashboard reporting tool to Hadoop (if even that). I can understand the temptation to rebrand an existing BI tool as a Big Data platform but it would be unfortunate if anyone actually fell for that.

Here in Idiro we like to differentiate between BI and predictive analytics – there are many companies offering BI tools of varying levels of sophistication. However, there are far fewer suppliers of predictive analytics platforms  (and even fewer still who provide predictive social network analysis like ourselves). In essence, BI tells you what did happen (i.e. after the horse has bolted) and predictive analytics tell you what will happen (while the horse is still happy in the barn). A smart company will use both.

But back to the definition of Big Data…some would argue that Big Data is all about analysing unstructured data such as blog postings, tweets and other such rubbish. Sorry, yes, I know there is useful information in there but there’s a lot of junk too. We prefer not to discriminate against data and believe that any data can form the input for a Big Data platform.

A word of caution lest anyone think that by installing some Big Data platform that all their problems will be solved. The analytics generated by any such platform need to be used to change business behaviour – this is probably the biggest challenge to the successful deployment of analytics within a company. Often there is political resistance within a company to the use of analytics that makes the Israeli-Palestinian problem seem like a walk in the park. Simply put, people and processes need to change if a company is going to capitalise on its investment in analytics.

As for the aforementioned teenagers, I think that when it comes to the adoption of behaviours that they find “beneficial” they exhibit a lot more openness to change than some large companies who desperately need to reinvent themselves. Big Data may or may not be a panacea for all a company’s problems but, once we step away from the buzz and the hype, what we see is that companies small and large, who intelligently leverage analytics for business really do get the edge over their competitors. Call it Big Data, call it analytics, the important thing is to call it right.

Aidan Connolly
Email: a.m.connolly@idiro.com