CRM Executive
London / £30000 - £36000
INFO
£30000 - £36000
LOCATION
London
Permanent
CRM EXECUTIVE
LONDON - HYBRID, 3 DAYS IN THE OFFICE
£30,000 - £36,000
THE COMPANY
This leading sports nutritional business is looking for a CRM Exec to join their CRM division. This brand operates on a global scale. They cater to professional athletes to gym goers. You will report directly to CRM Lead and support the wider CRM strategy
THE ROLE
As a CRM Executive, some of your main responsibilities will be:
- Supporting the omnichannel CRM strategy, with the focus of optimisng the current customer base.
- Work on developing the customer journey to ensure reduced churn.
- Plan & execute the email & SMS marketing calendar
YOUR SKILLS AND EXPERIENCE
The CRM Executive will have:
- Strong knowledge of any CRM system, they use Adobe and this is heavily preferred.
- Experience dealing with senior stakeholders within a business.
- Commercial awareness and excellent communication skills.
THE BENEFITS
- A salary of £36,000
- Comprehensive benefits package and flexible working.
HOW TO APPLY
Please register your interest by sending your CV to Tristan via the apply link on this page.
CONTACT
Tristan Bowler
Senior Recruitment Consultant
SIMILAR
JOB RESULTS
The More You Keep Customers Long-Term, The Better Your Business Will Do: A Q&A with Corin Rogerson | Harnham Recruitment post
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“I like thinking about how customers experience things and how you’re able to effectively tailor your business to them.”
We recently had the opportunity to speak with Corin Rogerson, a CRM Specialist and customer champion to discuss all things CRM.
Beginning in the digital space she has taken her holistic overview of customer experience with her throughout her career and built CRM programmes for some of the biggest brands on the market. So how has CRM changed during this time and where does she see it going? As we see a general trend towards digital first businesses, online platforms and integrated apps it goes without saying that CRM is having to follow suit. For Corin, potentially one of the biggest changes driven by this is this marketing technology landscape: “I think the main thing I’ve seen is when I first started in CRM there were lots of tools that were offering the ability to communicate with someone through one channel […] and now what I’m quite pleased to see is that some companies are building solutions from the ground up.”This shift from bolted together CRM/ESP’s to streamlined platforms offering the opportunity to build multi-touchpoint journeys now makes it far easier to build synchronised customer experiences. Hand in hand with technology is the ever-increasing presence of data in decision making, and a growing factor in successful CRM: “A few years ago everyone was talking about Big Data, and there are more tools able to process that data now”. But within this is the value that Data can bring bought about through “thinking about the Data that is actually important to you and what you can actually use, rather than just pushing everything in.”
But simply having the Data there isn’t enough to immediately achieve results and one of the biggest issues Corin has faced is around data latency and the impact this has on communication: “In the past if you had Data in 24 hours that was perfectly fine, but now you really need to know virtually in real time what a customer has done to communicate with them effectively […] for instance if a customer’s payment details have expired and there is a lag between them updates and an email going out it can be a really confusing communication.” However, that doesn’t mean that Data hasn’t played a large part in her successes. Customer Data has huge ties to personalisation (another noteworthy trend in the CRM space) and is often the best way to demonstrate the value a customer has to a business as shown through Corin’s biggest successes: “Where I’ve been really successful in a company or working on individual projects is always where the CRM team works really closely with the Data team. Over time you can put in really intelligent campaigns.”
So, what is the importance of CRM in today’s climate? Having experienced the power of CRM across businesses at different stages of their journey CRM is ultimately really important for growth. In the case of start-ups “the focus is very much on acquisition and that is partly because of the priorities in early life” but no matter the size of the business “it’s very expensive to acquire a new customer”. As such, Corin suggests bringing in a CRM team and shifting towards a culture of retention over rapid acquisition as soon as possible: “As soon as you bring a CRM team on boards […] you can start looking at your existing customer base and seeing how likely they are to repeat purchase […] the more you keep those customers long term, the better your business will do.”Her biggest pet peeve linked to CRM and growth? Data: “There’s nothing more frustrating than not having the right Data available”. Although the overriding advice is ASAP, it’s with the caveat of an adequate Data infrastructure to allow for the insights to be leveraged. It feels uncomfortable not to acknowledge the elephant in the room and the impact COVID-19 has had on how brands market to customers: “When the pandemic hit a lot of businesses had to take a step back and think, what are our values, what is our proposition and how can we help people in context to the pandemic.”In an ideal world this would then feed into the CRM team yet we’ve all experienced “empty examples of communications from companies who feel they have to say something about it […] and it doesn’t work, and I think it actually does damage to the brand.” Corin’s advice on this?”If I was in a CRM team that is what I would be thinking about. Making sure communication is relevant, it’s useful and it’s something that you will then be remembered for when everything is over.”If you’re looking for an opportunity in the world of CRM, or to build your Customer Insight team, we may be able to help. Take a look at our latest opportunities or get in touch with one of our expert consultants to learn more.
The Long Game – Sports Analytics and Social Media Insights | Harnham US Recruitment post
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The Eagles just took down a Super Bowl dynasty, the New England Patriots. They did it with a quarterback only three games in before the Bowl. In 2002, the Oakland A’s in a bid for the Championship won 20 consecutive games with, as quoted in the movie Moneyball, “an island of misfit toys.” Football, baseball, basketball, whatever the sport, New York is the home for league headquarters. The New York Metro area is one of only two cities in the country to boast eleven sports teams in the five most important professional leagues. Here, numbers, stats, and algorithms are just as important as plays, training, and wins. Okay, so wins are important. But, how do you get there? How do you know your play will hit a home run or make a touch down? It’s in the numbers, the data. Even fan engagement can offer insights across social media channels – every channel, fuel to the win, plus of course great players, well-trained, who go for the win.Sports Get Social (Media)Sports have always been social; a place for friends and family to gather and cheer on their favorite team. In the age of digital, sports teams and their players join the social media landscape to better engage with fans and businesses are paying attention. Social media value in sports translates to the transfer of power of popular players and teams to products. Something like the athlete on a cereal box, but on a much wider scale. For customized up-to-the minute dashboard analysis, companies spend anywhere from $50,000 to $100,000 to determine their social media measurements. Comparing their mentions, fan reach, engagement and so on to see how they measure up against other teams and players within a specific location or sport.As social media continues to preoccupy marketing and advertising executives in sports, decision-makers are digging deeper. They want to know what’s working, what isn’t, what to focus on, who’s being reached, and how effective their efforts are. Data is weighted depending on the sport, but across the board social media is quickly becoming one of the most important ways to speak to sports fans.
Sports Marketing Insights Though TV, radio, and in the seats are still valuable and viable, the sheer magnitude of social media fandom is on the rise. Wherever you are, you can check your favorite teams scores, find player stats, and compare notes with others around the world. The key selling point for marketers? Instant feedback. Marketers now have instant access to what’s working and what isn’t when it comes to social media. They’ll know immediately whether a brand campaign is successful or not and can gauge its effectiveness via comments and critiques. Insights via these channels allow businesses to see at once what might take them hours or days to compile via polls, surveys, or focus groups. Fan engagement insights are invaluable to not only launch follow-up campaigns, but to ultimately have user-generated content to spur engagement.In play, a team’s success is measured on the scoreboard, but in social media channels, teams, players, and brand successes are measured with fan engagement. Though not everything can be controlled, we would be remiss in not mentioning analysis of pain points and injury reduction through machine analysis. Pain Points While ultimately, coaches decide who is at risk for injury and must make the determination to keep them on or take them off the field, they must first understand the computer-generated analysis. As seasons progress, fluctuations in a player’s fitness and appetite for risk determine the probability of injuries.This type of analysis requires a level of computation only machines can process. But, if coaches don’t understand what they’re reading, they can’t make informed decisions. They need to know such variables as how the predictions and analysis were calculated as well as the exact effects of analytics on performance. They need to trust the numbers generated by the machine, then combine that with their domain knowledge and experience to make their decisions. Predictive injury analysis, fan engagement, brand awareness, and sports business executives can all benefit from insights gained through analytics. Marketing insights help to propel successful campaigns into the limelight and this knowledge helps to feed everyone’s bottom line.
Join the ClubMultiple revenue streams such as match day, broadcasting, commercial, and now digital are driving sports teams’ executives and clubs to a healthy bottom line. Fan data segmented by any number of factors include age, location, and gender while store sales and season ticket holders can be monitored to understand where and when sales are being made. Clubs use this information in their marketing campaigns to decide the best place for their stores based on demographics and fan behavior. By analyzing these results they can even boost ticket sales based on past results to balance profit margins through predictive analytics.The potential for analytics in sports has been utilized prodigiously in every sport from baseball to football to basketball and everything in between, yet its benefits are still up for debate. Data-driven insights offer a glimpse into the inner workings of teams as one unit, can help prevent injuries, as well as help individual players improve their game. When the dynamics come together the return on investment can be huge. Though the data must be translated for humans to understand, most sports clubs recognize data can create insights humans can’t replicate.Analytics may offer immediate insight once played, but investment in analytics is a long game. Affecting everything from player recruitment to injury prevention to business decisions, for some the debate of its benefits remain. Yet, as the jocks claim the money and fame, the back-office nerds are developing algorithms to help businesses determine everything from player picks to ticket prices.Want to join our club? We specialize in digital and analytics recruitment and currently have an opening in our roster for a Lead Marketing Scientist with a data-rich sports media firm in New York. For a list of all our current vacancies, check us out here.For the East Coast team please call 212-796-6070, or email newyorkinfo@harnham.com.For the West Coast team call 415-614-4999 or email sanfraninfo@harnham.com.
Using Data to Optimise Supply Chains
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Using data to optimise supply chains
The ripple effects of Brexit and pandemic restrictions continue to affect industries that are heavily reliant on supply chains.
Many manufacturers are still struggling to make up lost ground. For example, the Baltic Airfreight Index (BAI), which tracks prices for transporting cargo by air, is still down approximately 40 per cent from its peak, as its supply chain continues to heal. In this environment, ensuring that supply chains are running as optimally as possible, and are flexible enough to cope with evolving developments, has become paramount.
Data has long been the bedrock onto which these industries build their processes. Without an accurate, comprehensive view of the entire manufacturing operation such as product quantities, timescales, and other logistical detail, it’s impossible for executives to make effective decisions. In a 2022 Industry Pulse survey, manufacturing and distribution executives highlighted the criticality of real-time intelligence in managing their supply chains under volatile business conditions.
Various new technology powered by data allows businesses to continuously review their processes, and adjust to the ever-changing landscape. This, in turn, will have a wealth of positive implications such as diminished costs, reduced waste, and improved profit margins.
The amount of manufacturing supply chain data available today is staggering. While most manufacturers have now begun harnessing their data, many are still struggling to capture significant value from it. A 2021 study revealed that just 39 per cent of manufacturing executives had successfully scaled data-driven use cases beyond the production process of a single product.
So, how can organisations harness their data to improve their supply chains?
Data can help increase transparency
One of the main challenges faced by supply chains is a lack of transparency. Supply chains often span across multiple manufacturing and logistics operators with several tiers of suppliers, and because of this, data is typically collected and stored in separate silos.
As a result, it’s difficult for supply chain managers to get a clear and holistic view of crucial KPIs, such as service levels and costs. This means information about the real-time performance of end-to-end supply chains is often unknown. Or, if it is known, it’s reported infrequently, which can impact business performance. For instance, the malfunction of remote equipment could remain undetected resulting in exploding supply chain costs and lead times.
Transparency can be increased by ensuring that more information is accessible and therefore usable. New technologies like the Industrial Internet of Things (IIoT), for example, can collect remote ‘process data’, which might include warehouse temperatures or transportation waiting times, via sensors and then forward this to the cloud in real-time to inform decision-making.
And with the cost of IIoT devices and sensors plummeting, and 5G connectivity expanding worldwide, manufacturers of all sizes have the chance to cash in on capabilities like tracking shipping containers on their journey. Thereby enabling them to set realistic customer expectations, schedule production activities dependent on the incoming shipments, and swap to alternate suppliers to overcome delays.
Data assists in strategic planning
The implementation of supply chain analytics, allows vital conclusions to be drawn from this real-time and supply chain data, allowing businesses to effectively plan ahead. This can be roughly categorised into four buckets:
- Descriptive analytics uses historical manufacturing data gathered from suppliers, and customers data, to identify important trends or patterns.
- Predictive analytics models out a range of ‘what-if’ scenarios by analysing a variety of macro-level data including consumer demand, weather events, and staff shortages to accurately predict how these may impact a manufacturer’s supply chain or production capabilities. All of which will ultimately inform the creation of a robust contingency plan.
- Prescriptive analytics uses the results of predictive and descriptive analytics to suggest potential actions that a manufacturer could take to achieve predefined goals. For example, identifying weak links in the supply chain.
- Augmented analytics harnesses Artificial Intelligence (AI) and Machine Learning (ML) techniques to analyse huge, complex data sets from multiple sources to make highly accurate predictions. One new application of augmented analytics is the improvement of worker safety by using wearable sensors that collect data on worker health, stamina, and exposure to occupational hazards and alert managers when interventions are needed.
So, what can analytical techniques support a business with?
Demand planning and forecasting/resilience
Predictive analytics supplements historical data with data on current market trends and industry competition allowing for improved demand planning and forecasting. In a nutshell, this means that manufacturers can better align production with customer demand, improving efficiency and reducing waste, as warehouses will only stock what is needed.
Agility
The agility of a business’s operations relies on the amount of information it has and how accessible it is. Take data from manufacturing systems – it can inform decisions to accelerate production, adjust output parameters, or enable proactive equipment maintenance, as and when required. Similarly for managing vendors, ‘Dynamics 365 Supply Chain Management’ can connect to supplier catalogues and enable near real-time visibility of supplier processes. This helps businesses to understand and control costs through priority-based supply planning, make AI-supported inventory decisions, and automate warehouse operations.
Proactive risk management
Complex supply chains pose a significant risk for manufacturers, just one key supplier being out of action due to adverse weather can easily cripple production, resulting in costly delays. To overcome this, manufacturers and suppliers can opt to share data, allowing manufacturers to analyse supplier data to gain deeper insight into quality, on-time performance, and pricing. This knowledge gives manufacturers greater insight into each link of their supply chain, allowing them to renegotiate pricing, address quality concerns, or switch to a more reliable supply partner.
Whether you are looking for your next opportunity in the data industry, or need to build out a data team to optimise your supply chain? Get in touch with one of our team today who will be able to help.
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