By
The use of analytics is no longer limited to big companies with deep pockets. It’s now widespread, with 59% of enterprises using analytics in some capacity. And companies are capitalizing on this technology in several ways. For example, at our agency, we typically scrub big data for advertising insights for our clients. And many of the companies we’ve worked with revolve their entire market strategy around the insights pulled from new data.
According to a survey from Deloitte, 49% of respondents say that analytics helps them make better decisions, 16% say that it better enables key strategic initiatives, and 10% say it helps them improve relationships with both customers and business partners. But in order to take full advantage, you need to know how to get the most value from your data.
Data Quality Standards
There is certainly not a lack of data available. However, the quality of that data still leaves much to be desired. A study from the Harvard Business Review discovered that data quality is far worse than most companies realize, saying that a mere 3% of the data quality scores in the study were rated as “acceptable.”
This is problematic because low-quality data adversely impacts many areas of business performance. In particular, it can translate into incomplete customer or prospect data, wasted marketing and communications efforts, increased spending and, overall, worse decision-making. Therefore, improving data quality should be a top priority for all businesses.
There are a few ways to go about this but, in my opinion, as an agency owner, one of the best approaches is web data integration (WDI). WDI is a process that aggregates and normalizes data and presents visuals and other reporting that makes analysis easily digestible. WDI relies on a similar premise as web scraping but is far more comprehensive. It also has the ability to make data “intuitive” — something that’s essential for capitalizing on the massive volume of data that’s out there.
It allows you to take a large volume of data from a myriad of sources and break it down in a way that makes client analysis much easier to do. For us, if we’re looking to clean up data quality, this process helps us present data back to clients in a cleaner fashion.
Before formally choosing to implement WDI, businesses should first determine what specific goals they have for data sets and then decide whether an in-house solution or a managed service through a third-party provider is the better option.
Another way companies are fully leveraging data is through machine learning, where computer systems learn, improve and evolve as they take in new data.
Assessing Data Quality
So, how can you tell if you’re dealing with low-quality data? In a Harvard Business Review article, data experts Tadhg Nagle, Thomas C. Redman and David Sammon recommend the following key steps:
• Gather a list of the last 100 data records you used or created.
• Then, focus on 10-15 key data elements that are most integral to your business operations.
• Have management and their teams go through each data record and identify any noticeable errors. Examine the results. (In my opinion, an easy way to go about this is to create a spreadsheet with two columns — one for perfect records and another for records with errors.)
Once you look through the results, the quality level of your data should become obvious. If more than two-thirds of your records have errors, that’s usually a sign that data quality is hurting your performance and needs improvement.
Here are a few other data management tips:
• Move all of your data to a centralized database to create a standardized data architecture.
• Ensure your employees are up to date on all aspects of data best practices, including data entry, management, compliance and safety.
• Create data management hierarchies if you have multiple teams to keep it all organized and reduce the odds of a breach occurring.
• Designate certain team members to handle core data management.
Choosing The Right Tools
Data is one of the most valuable assets a business can have and potentially has a tremendous impact on its long-term success. That’s why it’s vital to utilize the right tools and technologies to fully leverage all available data and make it as accurate as possible.
Here are some specific things we look for when assessing tools/technologies for accurate data analysis:
• Data normalization for simple organization
• Shareable dashboards for streamlined communication between team members
• Fully mobile
• Third-party integration
When searching for tools, it’s wise to request a demo of any platform you’re considering to get a hands-on feel of how it works, what the dashboard is like, how intuitive it is and so on. Do you naturally like the look and feel of the product right off the bat? Or do you find the experience to be friction-filled? First impressions are everything, so you want to ensure the product feels right to you.
Final Thoughts
Analytics has come a long way in a relatively short period of time. It can aid in multiple aspects of operations and be a real game-changer for many businesses. But to get maximum results, companies need to know how to properly utilize this technology, improve the quality of their data, and effectively manage it. Those who are able to do so will have a considerable advantage over the competition, and be poised to succeed in 2019 and beyond.
Feature Image Credit: Getty
By
Partner at K&J Growth, serving some of the world’s largest companies through smarter marketing | Partner at Rugby Bricks.Read Kale Panoho’s full executive profile here.
Sourced from Forbes
By
A new study shows just how much consumers want brands and culture to mix
Insight-rich results
The study found that brands can become more relevant by embracing culture by staying current, demonstrating knowledge of consumers and giving back. When people are deciding which products and services to buy, they’re not only thinking of basics like price and quality—or even more amorphous concepts like reputation. They are also assessing just how much a brand reflects their interests and supports the issues they hold close to their hearts.
Incredibly, a brand’s cultural involvement makes up a full 25 percent of a consumer’s purchase decision. That means being involved in culture is a significant consideration when people are weighing whether or not to buy something, alongside other factors like positive brand perception, price and quality. It’s a finding that should make marketers rethink their focus and strategies, since cultural relevance can be established with one campaign, whereas other factors are relatively more intractable.

What does this mean for marketers?
Go where the most leaned-in and influential people are already gathered: A key revelation of the study is that while culturally passionate consumers tend to be younger, what really sets them apart are their media habits. Social media usage is a 25 percent stronger indicator of cultural passion than age. According to our study, culture-focused ads work harder on Twitter than on other premium sites, where audiences of true tastemakers are most engaged and most receptive.

Have a strong POV in your ads: Culture-focused ads succeed in positioning brands as relevant. They also position them as socially responsible and innovative. And they create a more memorable experience for consumers.
This new research makes a strong case for brands to acknowledge, and even actively improve, the culture that permeates all of our lives so fully. And expressing their engagement with culture on platforms like Twitter is the best way for brands to join the liveliest conversations of the day.
By
E.J. Samson is the lead content strategy manager for Twitter’s Global Business Marketing team. Follow him on Twitter @ejsamson.
Sourced from AdAge
Personalised advertising already stalks us across the web, and it’s coming to our TVs, with Channel 4 the latest broadcaster signing up to use Sky’s AdSmart to target commercials. While such a system isn’t quite as invasively personalised as the behavioural advertising clogging up the internet in order to show us shoes we’ve already bought, it could have a big impact on television – and risks being rather creepy.
AdSmart is Sky’s system for targeted, addressable ads, which are commercials that can be swapped out and personalised based on location or other personal data – even in live-broadcast, linear TV. Sky has used the platform on its own channels since 2014, and has this year signed up Virgin Media and Channel 4 to do the same.
For viewers, the benefit is not being shown irrelevant ads – Sky won’t show you ads for its broadband if you’re already a customer, for example – and Sky points to research that suggests there’s a 48 per cent drop in channel switching when such targeted ads are shown. For businesses, small companies can target a specific, hyperlocal catchment area rather than throw away money on nationally shown commercials, opening up TV advertising to smaller companies.
And for broadcasters, the benefit is they can charge more, perhaps as much as ten times more, for what they say are more effective ads – helping to claw in more cash as advertising revenues stall. “Better targeting can be beneficial for both advertisers and viewers: it can not only increase ad return on investment for advertisers, but also deliver more relevant information to viewers,” says Yiting Deng, assistant professor of marketing at UCL. Richard Broughton, researcher director at Ampere Analysis, suggests by a rough estimate it could bump revenue at Sky by as much as 10 per cent and across the wider industry by 2 per cent – it’s positive for broadcasters, but its financial impact is limited.
No wonder then that targeted television ads are already in use with on-demand services; Channel 4 earlier this year rolled out a tool letting brands use their own data to match ads to audiences. But swapping out ads is a bit more difficult with live television. “The key technology is combining what is called addressable advertising, which is personalised, with programmatic systems, which is enabling the purchasing of ads automatically,” says James Blake, director of the Centre for Media and Culture at Edinburgh Napier University.
According to Sky, AdSmart turns your set-top box into a local ad server, downloading and storing commercials deemed relevant based on the data the company holds on you. When watching an AdSmart-enabled channel, those ads will be swapped into the commercial break spot; if there are no AdSmart ads available – or you’ve opted out – a generic commercial is shown instead.
To do this, AdSmart and broadcasters that use it require data about viewers. That could be limited, as a local small business could target a handful of postcodes, with a different ad shown to everyone else, with no personal information required. Sky says that location is a key attribute, though there are thousands more, noting that Huddersfield Town Football Club advertises season tickets locally; there’s not much point in showing that commercial to football fans in Scotland, after all. Location can also be used to target ads more carefully using demographic information; if a neighbourhood is more likely to have family homes, showing ads targeting parents makes more sense.
But targeting those ads more precisely – such as showing pet food ads only to those with cats and dogs – requires more data, which broadcasters purchase from third-party data brokers. Sky, for example, says it can select viewers in groups of 5,000 or more based on age, location, lifestyle, and “even if they have a cat”, using Sky’s own customer data, information provided by the company wishing to advertise, and data bought in from third-party brokers such as Experian, Dunnhumby, CACI, 20ci, Mastercard, Emma’s Diary, and Game. Companies such as those have already been targeted with GDPR complaints for exploiting our personal data and selling it on to marketing companies. If you want to know what data Sky et al have gathered on your family, you can file a subject access request.
Technically, it’s possible to make addressable ads more tightly personalised than those groups of 5,000 used by AdSmart, but there’s a danger that could put viewers off, notes Blake. “I think TV companies and broadcasters need to be careful how they use personalised advertising,” he says. “There’s a risk these adverts can be creepy.” Blake points to an experiment in 2017 when viewers on the Channel 4 app were shown adverts with their own names, which some people found “a little bit creepy”, he says.
There’s another reason TV commercials aren’t likely to get quite as personal as online ads: they cost more to make. “You’ve got additional costs for producing high quality TV adverts – the creative process in itself is quite expensive,” Broughton says. “So this is about refining your spend, as opposed to micro targeting a specific segment.”
While there’s merit in avoiding ads for products you’d never buy, such targeted ads could also be used for political marketing – and that raises concerns for democracy when we’re not all seeing the same message, though Blake notes that broadcast television advertising in the UK is heavily regulated. “That’s one of the big reasons why TV is trusted in the way it is,” he says. “But we need to be aware of the risks because TV adverts can be hugely powerful and we don’t want political campaigns and parties to misuse that. There is a danger that you end up in a bubble of like-minded people with like-minded messages, and don’t get exposed to sentiments on the other side.” However, in the UK, such commercials are banned, with unpaid allocated spots given to the parties instead.
And that’s another reason TV ads aren’t likely to be as invasive as online counterparts: they’re heavily regulated. Broadcasters face tighter regulation than online advertisers, and GDPR should limit how personal data is repurposed for marketing. “Addressable advertising in TV took a hit when GDPR came on board,” says Blake. “Before GDPR, there was a lot of discussion about how cookie data [from web browsing] could feed into adverts. And I think GDPR made that process take quite a big hit.”
Both Sky and Channel 4 say they follow GDPR’s rules, and both allow viewers to opt-out of AdSmart, with Sky adding that any “special category data”, such as information about your health, needs consent to be processed by AdSmart.
If such ads do come off as creepy, you can opt out – and not only of AdSmart, but the broadcasters themselves, something they’ll be wary of. As Broughton notes, angering customers doesn’t have much value to broadcasters such as Sky that can cost up to £70 a month. “It’s not worth jeopardising that to get a few extra pence out of an advertiser,” he says, predicting that “they’ll err on the side of caution.”
Feature Image Credit: Getty Images / WIRED
We know that exceptional content is what makes a brand. We also know that analysing our data to very specifically target audiences is crucial for great ROI. But we rarely put the two together and use the data available to actually analyse what content works – and why.
Yet knowing exactly why content works can give us that winning edge. And, luckily, the ability to see what indisputably resonates the most with our audience – and drives our bottom-line – is already in our hands.
The state of play
In the climate of the current ‘data boom’, audience targeting naturally takes precedence, with the majority (55%) of marketers saying ‘better use of data’ for audience targeting is their priority in 2019, according to Econsultancy.
It makes sense. On a daily basis, we’re faced with countless blogs, podcasts, speakers and everything in-between promising that if we perfectly optimise our targeting, our messaging will beat the daunting odds of the 0.9% CTR cited by WordStream. And so, we dedicate hours and hours every week to creating personas, hypothesising about audiences, segmenting users and running lengthy A/B tests to find the piece of content that our audience love. We add to our already-complex marketing stacks tools that tell us what messaging has been more successful, in order for us to optimise.
But when we do find that winner, do we know why it works? Do we know exactly what features caused the higher CTR? Do we know how we’re going to recreate it in our next campaign, to make it better, even?
This lack of knowledge – despite all the tools and techniques we use to offer insight – is what we at Datasine call the ‘black box’ because when it comes to understanding why, we are left in the dark. Just looking at results doesn’t give us the insight needed to truly understand content preferences in an actionable way.
Semantic content analysis
To crack open the black box, we need to start conducting in-depth semantic analysis of our content. Only then can we begin to truly understand why some content resonates and some doesn’t.
As experienced marketers, we come prepackaged with a deep understanding of – and fascination with – psychology and our audience, meaning we’ve already got the skills on paper to analyse our content. It’s simply a matter of breaking it down into parts. We’ll look at this in terms of images and text.
If you want to analyse your imagery, you can take all the image assets you’ve ever created and note down the particular elements you used in each, then check to see if there are any patterns which relate those choices to your ad performance.
For example:
- Did you use a photo of your product outdoors? Or in the showroom?
- Were people visible in the shot?
- What was the size of the text, and the colour of any overlays or CTAs?
It may even be worth inviting a panel to judge your images on the emotions that they evoke, or photographers to assess the quality and composition of the shot.


You can do the same for text content, approaching this by categorising how you describe your product or service. For example:
- Do you appeal to your product’s ease of use?
- Are you emphasising your innovative credentials?
- Do you use particularly casual – or formal – language?
With this process, we can see which types of content are receiving the most engagement. And we can use these features to keep creating great campaigns that we further optimise as our understanding of customer content preferences grows.

Scaling content analysis
If we have just a few campaigns on the go, content analysis is easier, but it gets harder as we scale. It stops being practical to expect humans to spend days, weeks, even months labelling what goes into each piece of content. Here’s where machine learning and artificial intelligence (AI) come to the rescue.
AI models can extract all of these elements in seconds by analysing image or text semantically to look at content like humans do. That way, we can cut back on lengthy, expensive A/B testing, and get rid of guesswork once and for all – a vision we at Datasine are working toward. Our AI platform Connect (formerly Pomegranate) automatically identifies the most effective content for your audience.
By embracing semantic content analysis and working collaboratively with AI, we can feel confident in understanding exactly what content is going to work before we hit send.
Sourced from The Drum
By
Developing a holistic data strategy
Enterprises of all sizes, all over the world, have now recognized that data is an integral part of their business that cannot be ignored. While each enterprise may be at a different stage of their personal data journey – be it reducing operational costs or pursuing more sophisticated end goals, such as enhancing the customer experience – there is simply no turning back from this path.
In fact, businesses are at the stage where data has the power to define and drive their organisations overall strategy. The findings from a recent study by Infosys revealed that more than eighty-five percent of organisations globally have an enterprise-wide data analytics strategy already in place.
This high percentage is not surprising. However, the story does not end with just having a strategy. There are numerous other angles that enterprises must consider and act on before we can deem a data journey as successful.
Developing a data strategy
First, enterprises need a calculated strategy which covers multiple facets. Second, the real life implementation of the strategy must be seamlessly carried out – and this is where the challenge lies for all enterprises.
Consider having to create a comprehensive and effective strategy for your company. Data strategy is no longer about simply identifying key metrics and KPIs, developing management roles or creating operational reports, or working on technology upgrades. Rather, its reach extends to pretty much all corners of the business.
In short, data strategy is so tightly integrated with business today, that it is in the driver’s seat, which is a momentous shift from more traditional approaches of the past.
What are the characteristics of a good, strong data strategy?
Creating a good, strong data strategy begins with ensuring complete alignment with the organisation strategy. The data strategy must be closely aligned to the organisational goal, be it around driving growth or increasing profitability or managing risk or transforming business models.
Not only that, but the data strategy must be nimble and flexible, allowing periodic reviews and updates to keep pace with wider changes in the business and market. The data strategy should be able to drive innovation, creating a faster, better and more scalable approach.
A strong data strategy must be built in a bi-directional manner so that it can enable tracking of current performance using business intelligence to provide helpful pointers for the future. This approach is only possible if organisations choose to adopt a multi-pronged data strategy that encompasses people, technology, governance, security and compliance. Importantly, organisations must also choose to adopt an appropriate operating model.
Taking a holistic approach to data
A holistic approach includes developing a defined vision, having a clear structure around the team and factoring in the current skill set of the team. This is in addition to considering what the enterprise can reasonably anticipate in the future and identifying mechanisms to successfully drive the change across the organisation.
The technology component involves having a distinct vision, assessing the existing solution landscape, all the while being cognizant of the latest technological trends and arriving at a path that fits well with overall organisational goals and the technology vision.
Governance, security, and compliance are other critical aspects of a good data strategy. Integrity, hygiene and ownership of data, plus relevant analytics on the data to determine the Return On Investment on data strategy, are all essential steps which cannot be forgotten. We cannot overstate the importance of security.
Adherence to compliance has assumed significance with various regulations in play all over the world, such as GDPR in Europe and new data privacy laws in California and Brazil for example.
In essence, the data strategy must define a value framework and have a reliable mechanism to track the returns to justify the investments made. About fifty percent of respondents to our survey agreed that having a clear strategy chalked out in advance is essential to ensuring an execution that is effective in practice and goes off without any hiccups.
Identifying the best strategy is essentially pointless if the execution falters
Many obstacles have the power to prevent the flawless execution of a data strategy. Copious challenges in the technology arena can arise in various forms, for example: having the knowledge to choose the right analytics tools, lack of availability of people with the right skill set, upskilling, reskilling and training the workforce with the necessary skills for the world of tomorrow and so on. Most of the challenges articulated by respondents to the Infosys survey arose in the execution phase of a data strategy.
While these challenges may appear daunting in the first instance, they can be addressed with careful planning and preparation. Being prepared and equipped for multiple geographies, multiple locations, multiple vendors, talent acquisition and good quality training are just some of the numerous possible ways companies can begin working towards smooth execution of their digital strategy.
Feature Image Credit: Image credit: Pixabay
By
Gaurav Bhandari, AVP and Head of Data & Analytics Consulting at Infosys.
Sourced from techradar.pro
By Teradata and the Forbes Insights team
In a world overflowing with siloed petabytes of data, understanding can come only with data analytics that are seamless and all-pervasive.
Having access to all the data at every point in time leads to insights and drives powerful outcomes that make the difference between good and great.

Imagine a patient being rushed to the ER after an accident or a cardiac arrest and not being able to get a critical test with diagnostic equipment in these split-second, life-and-death scenarios. Maximizing availability, or uptime, of equipment, therefore, assumes top priority.
Healthcare 4.0 is all about gathering relevant and valuable data and using it in applications that translate into improved healthcare management, efficiency and cost-control. In particular, using data analytics to bolster predictive maintenance of equipment can help ease the workload of healthcare service providers so that they can spend more time focused on their patients.
The Scenario:
Siemens Healthineers is a global medical equipment manufacturing company with a presence in more than 70 countries. There is an installed base of about 600,000 active systems around the world, allowing for roughly 240,000 patient touch points every hour.
Many of the systems are remotely connected to Siemens Healthineers, e.g. for the purpose of predictive and reactive maintenance. The logistics of managing the significant amount of machine data generated is staggering.
The Challenge:
Modern medical equipment is typically highly complex with a lot of specialized parts. Healthcare providers invest in such equipment in order to provide excellent care to their patients. When the equipment fails, it not only inconveniences patients who need to reschedule their tests, it also proves to be challenging for healthcare providers who want to provide the best possible care.
Access to real-time data processing becomes absolutely vital to increase uptime of the equipment, operational efficiency, productivity and cost-effectiveness, and to decrease service parts usage, shipping and inventory. It’s a complex challenge to connect people, machines and data in a heavily regulated industry and rapidly moving IoT trends. And all of that in compliance with industry-specific and general data privacy laws, such as the EU General Data Protection Regulation.

Siemens Healthineers leverages Teradata to aggregate technical data from devices, both machine and process data, along with service parts and labor efforts to enable better outcomes at lower costs for customers.
“By transforming our data assets into concrete actions for our global service organization, we reduce the extent of technical expertise needed to maintain a system,” says Stefan Meiler, head of data governance and analytical services at Siemens Healthineers. “We avoid first-level onsite troubleshooting, optimize the service delivery process and minimize productivity losses from downtime situations for our customers.”

Faced with the challenge of diverse datasets siloed into machine data, service data, sales data and customer-related data, Teradata helps Siemens Healthineers put it all together in one data analytics software platform, Teradata Vantage. Once all the data is combined, Teradata connects the dots so that it can be used effectively for analytics by creating the bigger picture.
“Transforming data into value requires multiple development iterations while leveraging innovative, scalable and easy-to-use technologies. Our data stewards are transforming a wide variety of data assets into curated, single point-of-truth datasets,” says Dr. Mirko Appel, head of analytical services at Siemens Healthineers. “On top of these datasets, our data analysts develop dashboards to create transparency on our global installed base and service operations, while our data scientists are leveraging this transparency to automate data-driven services by applying artificial intelligence. Teradata Vantage enables us to accelerate all of these iterations while providing a fast, reliable and scalable backbone within our global organization.”

About 15 years ago, Siemens Healthineers invested in a secure remote services infrastructure that enables a comprehensive understanding of the state of their products — how, where and when common part failures occurred.
This not only minimizes equipment downtime but also provides substantial savings by avoiding sending technicians out to make repairs that were not needed in the first place.
This move from a reactive to a predictive model that anticipates service needs in advance has successfully translated to a higher first-time fix rate. It has also created opportunities for new types of service contracts with their customers.

Siemens Healthineers works with Teradata to create smart data assets to aggregate and consolidate the data in a ready-to-use form for its data analysts and data scientists so they can focus on discovering insights from the data. Using predictive maintenance for superior asset utilization has optimized equipment uptime. The increased operational efficiency has helped them provide answers to their customers even before they had thought of the potential issue, leading to high levels of customer confidence and satisfaction.
“The application of pattern recognition algorithms on machine data has transformed our service delivery towards a proactive approach: We are now able to identify certain system failures up to 21 days before they have an impact on the machine’s performance,” says Torben Scaffidi, head of lab operation analytics at Siemens Healthineers. “By this, we can increase the efficiency of our service delivery significantly and our customers are pleased with more valuable uptime to deliver care to patients. Win-Win for everyone: Siemens Healthineers, our customers and the patients.”

The amount of data that will be generated today and tomorrow will continue to grow exponentially. What will the next use case be? What will the next data format be? How to automate processes through machine learning for flexible solutions as the business expands? For answers to broader issues like these, Siemens Healthineers needs a global partner like Teradata to grow with.

Heavy regulations surrounding the healthcare industry as well as stringent data privacy laws add to the challenges of providing quality healthcare. Keeping track of the rapid changes in trends outside the healthcare industry, especially when it comes to the Internet of Things, is extremely challenging. Teradata operates in a wide range of industries and this also helps Siemens Healthineers benchmark themselves not only against the best companies in their sector but the best companies across all industries

As a company that is constantly innovating, Siemens Healthineers has a vast array of new and emerging R&D initiatives. With all these great new products comes the challenge of keeping track of the data coming from these new technologies. These may deliver new data structures and new predictive models. Learning from previous products and designing new data structures into new systems becomes crucial to data analytics in the future.
Answers must lead to better outcomes. Siemens Healthineers is looking at the next level of customer engagement by engaging online with customers interactively. The answers that they have through their data will also be at the fingertips of their customers so they can have a better understanding of their products and provide better outcomes for their patients.

At the heart of data analytics is the ability to transform vast amounts of data into actionable insights that organizations around the world can use to drive powerful outcomes. Better-informed decisions generate confidence, improve efficiency, nurture creativity and empower people to think of unique ways to push the envelope for social good.
By Teradata and the Forbes Insights team
Sourced from Forbes
Outset Agency, Basement 7 Pembroke Street Upper
Outset Agency seeks a highly motivated, creative and skilled Senior Account Executive to join our growing team, who will have a particular focus on the Creative Campaigns area of our business.
We are a new-age agency that focuses on how audiences and businesses connect. We work directly with both brands and agencies, helping them to achieve their goals.
Our work is focused across 3 key areas; Creative Campaigns, Influencer Marketing & Live Experiences.
The successful candidate will have experience working within the client services area of a marketing or media agency and have a strong knowledge of all the different marketing functions across digital, content, experiential and beyond.
The Senior Account Executive will be responsible for managing a portfolio of client accounts, as well as assisting the Key Account Manager on other projects.
Responsibilities
Responsibilities:
- Liaising with clients on a daily basis – with the Client Services team the lead point of contact on all Agency work
- Plan, develop and assist in the delivery of client campaigns and projects
- Plan and manage client budgets and advise on campaign elements and distribution channels
- Internal project management of Agency’s work across Digital, Content, Influencers and Events
- Supplier management and building business relationships
- Creation of client proposals
- Working closely with and reporting into the Key Account Manager on all Agency work
Requirements
Requirements:
- Minimum 3 years of experience working in Marketing or a related field (preferably Agency side)
- Strong understanding of current online and offline marketing concepts, strategies and best practices
- Ability to prioritise tasks and focus on multiple projects and deadlines simultaneously
- Strong presentation skills
- Excellent communication skills with the ability to interact professionally with clients and business stakeholders
- A creative thinker – we want someone that is resourceful and has the ability to think outside the box
- Ambition – we are young company that is moving and growing quickly, there is a huge opportunity for personal growth within the business for the right candidate
Click HERE to apply for this job.
Brandface, 47 Terenure Road E, Dublin
InSight Marketing is one of Ireland’s top independent Marketing Agencies, specialising in Shopper, Promotional, Digital & Live Marketing we work with the best brands in the country and in the world, creating hard working marketing campaigns that deliver an action and a reaction.
One of our Client Service Teams is expanding to meet the needs of our growing client base and we are looking for a brilliant Account Executive to join the team immediately.
You are either an Agency experienced Account Executive who is ready to fast track their career working on great brands, in a great team OR a top notch graduate who has already done an Internship in a Marketing Agency and can demonstrate the right attitude and the right skills set for the job.
Either way, you need to love the world of Marketing Agency and thrive on the pressure that comes with delivering flawless Campaigns and Brand Experiences.
Sounds like you? Then we want you on our team! There is a great package available for you!
Requirements
- Strong oral, written, and verbal communication skills
- Exceptional administrative skills
- Strong organizational skills with emphasis on time management
- Ability to work independently
- Strong attention to detail
- Exceptional proficiency with Microsoft Excel
Click HERE to apply for this job.
Xanadu, Cork
Reporting into our Chief Marketing Officer, you will help shape Matchbook’s search offering, ensuring the team and agency is managed well and keeps up-to-date with all industry developments. You will work across a range of channels, leading Matchbook’s strategy across the full paid media mix.
To be considered for this role, you must have be operating at a senior level within paid media. You will have management experience and be able to operate both strategically and at a hands-on level. Ecommerce experience is essential.
This is an excellent opportunity for an experienced and senior paid search professional to really mould Matchbooks product and offering.
Ownership overview:
PPCAdwordsSEO
Paid Social VODLanding pages
App store page
What will I be doing?
- Formulate and deliver the digital marketing & growth strategy to deliver on acquisition and retention targets.
- Develop, implement and manage the company’s digital strategy across channels such as Pay Per Click and SEO.
- Assist with the execution of Integrated Marketing campaigns to help raise awareness of Matchbook’s products.
- Analyse and optimise the conversion effectiveness of digital platforms and campaigns.
- Drive the implementation and adoption of key digital marketing tools (e.g. Analytics & Tracking applications) to continuously improve results and raise awareness of marketing / business KPIs.
- Manage all aspects of relationships with third party vendors and digital agencies and ensure their efforts are aligned with the digital marketing strategy.
- Act as the technical link between Marketing and Product teams, mapping out marketing technology capabilities and requirements in terms of in-house and third party systems, tools & technologies in an effort to boost acquisition, retention, and improve the betting experience of users.
- Responsible for budget planning, forecasting, monitoring of spend and channel performance, and reporting of performance to the wider team.
- Keep up to date with the latest digital marketing best practice.
- Manage, train and develop a digital marketing team and ensure best practices are followed.
What are we looking for?
- 3 to 5 years Digital marketing experience
- Specialising in paid acquisition and retention across PPC, Search, and Social
- Expert in search engine optimisation with proven track record of increasing organic search visibility and traffic
- Analytical, numerate, a commercial focus, and strong attention to detail
- Track record of building successful digital campaigns
- Interest in sports and betting preferable
- Ability to work collaboratively in a team environment as well as independently.
Xanadu is an equal opportunities employer