A hotel marketer’s guide to CRM

Typically, the marketing department plays the lead role in CRM, acting as the primary user and key operator of CRM software and managing guest communications and data.

As the guardian of the hotel’s brand, the marketing manager ensures that all guest communications are on brand and on message. Additionally, as a primary generator of demand, they use the CRM system to find opportunities to drive revenue and increase profits.

The marketing manager also acts as data scientist, extracting data and running reports to keep colleagues informed of trendsand patterns in guest behavior and preferences.

Key areas of responsibility for the hotel marketer

CRM administration: Oversees the implementation of CRM software, staff training, testing and maintenance, and acts as key operator and liaison to the CRM provider.

Planning: Works with the CRM team to set objectives, strategies and KPIs for the coming year and align them with marketing activities. Creates an annual calendar of marketing campaigns to keep the hotel top of mind, boost occupancy during periods of low demand, and drive higher ADR during periods of high demand.

CRM evangelist: Ensures that all staff understand the value of CRM to the hotel, use the software to its fullest capabilities, and input data correctly. Branding. Ensures that all guest communications are consistent with the hotel’s branding, including messaging, tone and visual appearance.

Messaging: Works with the CRM team to create templates and customized emails, including confirmations, pre-stay emails, promotional offers and newsletters.

Segmentation: Creates targeted subscriber lists based on variables such as location, interests, nature of travel, rate code, booking source, time of stay, stay frequency and total spend.

Marketing campaigns: Works with the revenue manager to identify revenue opportunities and sends customized offers to subscriber lists to achieve objectives.

Template updates: Updates email templates promptly to reflect changes to staffing, cancellation policy, check-in procedures and other details.

Loyalty programs: Oversees guest loyalty initiatives, including program membership, guest recognition, and tracking of stay frequency and total spend.

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Article Credit: HN

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Accenture to oversee SAP roll-out of US chocolatier Hershey’s

Famous US chocolate maker Hershey’s has signed Accenture up to support its SAP Hana S/4 implementation. The firm will work to help Hershey’s roll out the in memory ERP system, as the foods group looks to boost its growth, while reducing operational costs.

According to a recent report by Gartner, as many as 30% of service centric companies will move the majority of their ERP apps to the cloud by 2018. As a result, consulting services aimed at helping professional services providers leverage new ERP solutions from companies such as SAP are in demand.

Another aspect of the growth in SAP consulting is the continuing roll out of the enterprise resource planning (ERP) giant’s S/4Hana system – which is also available on cloud, alongside more traditional on-premises and hybrid deployment models. Billed as SAP’s “most important release in 23 years” when it was announced, S/4Hana was intended to be easier to use and administer while helping to solve more complex problems and handle vastly larger amounts of data than its predecessors.

The Hershey Company

Chocolate manufacturer The Hershey Company has become the latest in a list of global firms looking to leverage S/4Hana to this end. Hershey’s – the company behind such well-known products as Reese’s Peanut Butter Cups and Hershey’s Kisses – is a long-term SAP user, with its first implementation of SAP’s R/3 ERP package, in 1999.

It retained SAP despite initial troubles, when the £72 million ERP project caused order processing problems that hampered the company’s ability to ship products to retailers at one of the busiest times in its business cycle. The problems caused the company to fall short of its third-quarter sales target by £65 million.

Three years later and after consolidating the processing of more than 95% of its revenue and business transactions within a single system and increasing consistency, visibility and real-time access to critical business information, it upgraded mySap.com. Now, the company wants to reduce its costs and increase sales via the implementation of the in-memory version of SAP’s Business Suite ERP platform technology.

In order to achieve its goals, the confectionary conglomerate contracted outsourcing giant Accenture. The firm, which was also recently enlisted by the Canadian Government for its technological expertise, will aid the roll out of the ERP system, as part of a programme to make manufacturing and supply more efficient and better understand what customers want.

Speaking on the hiring of Accenture, Terry O’Day, Chief Product Supply and Technology Officer at Hershey’s, said, “This will enable us to increase competitive advantage and support our growth ambition through greater collaboration and innovation, as well as service delivery built around the needs of our customers. We selected Accenture for its understanding of our industry, technology credentials and proven track record in delivering enterprise transformation at scale.”

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Article Credit: Consultancy

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You know ERP, CRM, HCM? Here comes BSM – Business Spend Management

Recalling the history of TLAs in enterprise IT – ERP, CRM, HCM – Coupa CEO Rob Bernshteyn kicks off a 3-part introduction of BSM – Business Spend Management

The business world seems to love acronyms, maybe nowhere more than in the technology industry, and maybe none so much as the TLA (three letter acronym).

Acronyms certainly enhance recall, and they save time, space and effort in communication. Of course, they are shorthand for the name of something and as such, they help define it, creating a common understanding such that people can connect mentally to the thing without having to describe all of it.

If you can give something a strong, meaningful name, and encode it into an acronym that stands the test of time, it’s a good indicator that you’ve done something powerful in your industry. That’s why, as I’ll explain in this three-part series, we at Coupa are laying claim to the acronym BSM, for Business Spend Management.

It’s time for our category of information technology, and the work of professionals in this field, to have a name and a TLA that can stand together with ERP (Enterprise Resource Planning), CRM(Customer Relationship Management), and HCM (Human Capital Management). When you add BSM to the other three, these functions collectively and exhaustively address the core operating processes of every organization.

Not just BS software marketing

Is this just Bullsh*t Software Marketing? No, but one could argue that it used to be. BSM was previously claimed by vendors of Business Service Management:

A category of IT operations management software products that dynamically links the availability and performance events from underlying IT infrastructure and application components to the business-oriented IT services that enable business processes.

In March of 2016, Analyst firm Gartner pronounced business service management dead, stating that it:

… has not delivered on its promises of prioritizing, communicating and focusing I&O (Infrastructure and Operations) resources on the functions critical to the business.

I’m not here to dance on the grave of business service management, but there is a point to be made. The promise of business service management was unkeepable. No single solution could keep up with the pace of technology change and monitor and manage all the data and technology in the enterprise, and no TLA could change that.

But, TLAs such as ERP, CRM, and HCM have achieved lasting traction in the marketplace because they accurately represent marketplace needs and solutions that deliver real value. These names matter because they encourage companies to think bigger and more holistically about their processes, and practitioners to think bigger and more broadly about their roles within them.

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Article Credit: Diginomica

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Are Your Data Analytics Making You Smarter Or Overconfident?

According to a recent Harvard Business Review article, big companies are embracing analytics in 2018, but most still don’t have a data-driven culture. Furthermore, if I were to ask you if your company is data-driven, there’s a high probability that you’d say yes — despite substantial industry exaggeration. This is because the industry is only now beginning to put specific parameters around what it means to truly be data-driven versus, say, data-influenced or data-aware.

Many companies confuse the art of data collection with the disciplined science of data analytics. Having access to siloed reporting structures from Facebook, Google and your various marketing, sales and CRM platforms is not the same thing as being able to intelligently answer a question — backed up by data — about your customers and their buyer journeys.

Time is money, and your data speed provides a competitive advantage.

The vast majority of big data is unstructured, which means there’s a fair amount of data wrangling involved before you can analyze, build a hypothesis and test your understanding of what the data is telling you. Even with the help of artificial intelligence, there are often time-consuming steps required to break down the data silos to deliver meaningful and actionable insights from your data.

What’s worse, the larger the company (in terms of the number of employees), the deeper the silos tend to run. The social media team, for example, tends to myopically obsess over social media success metrics without having a deeper understanding of how their efforts fit into the overall customer journey from initial discovery to repeat purchase behavior.

This is why so many companies authentically believe they are data-driven, yet most are just beginning to fully comprehend what data is truly meaningful, how to navigate through all of it and, most importantly, how quickly they can act upon the insights once they are discovered.

Understand the digital analytics value chain.

A deeper understanding of your customer behavior is usually the most important insight. As business leaders, we tend to focus on metrics such as bounce rates and conversion metrics, but how do these metrics actually translate into truly understanding our customers? Over the past decade, we’ve gotten really good at reporting the actions our customers take, but by and large, we’re still pretty far from truly understanding our customers and their needs.

The goal of any analytics solution is not to track customers. The goal of data analytics is to understand the needs of our ideal customers and to begin applying our learning as we deepen our relationships with them.

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Article Credit: Forbes

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Democratising data analytics through automation

In the past, data analytics was the preserve of big business, reserved for those that could afford technology costing thousands of pounds and had the budget to employ teams of data scientists.

But those days are gone – we are now experiencing a democratisation in data analytics.

Universally accessible insights

Research by Gartner has found that more than 40% of data science tasks will be automated by 2020, by what it terms “citizen data scientists” (those whose job function is outside the field of statistics and analysis).

Gartner predicts that citizen data scientists will surpass data scientists in the amount of advanced analysis produced by 2019, resulting in increased productivity and business performance due to the broader usage of data and analytics.

“By using technology to automate complex analytics, retailers are able to expand the number of data sources to generate actionable insight”

This growth in citizen data scientists is being driven by evolving technology that is automating the hard work of data analysis.

By using technology to automate complex analytics, retailers are able to expand the number of data sources they use to generate actionable insight, without increasing their headcount or technical knowledge and expertise.

This will help them stay ahead of the competition and, in turn, allows data scientists to shift their focus on to more complex analytics.

Automating data normalisation

New data collaboration technology is intuitively designed to make comparing and analysing datasets quick and easy.

The AI-powered technology removes the need for datasets to be manually changed so they are in the same format.

“Different formats are automatically recognised and transformed so they match and can be analysed together”

For example, different companies may store customer age differently – one as date of birth and one as an age range.

Different formats are automatically recognised and transformed so they match and can be analysed together.

This enables a simple and fast process for the generation of insights.

It’s time for retailers to seize the initiative as the field of data analytics and integration becomes democratised by new technology, source the best datasets for their business and act quickly on the collaborative insight they deliver.

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Article Credit: RW

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Reshaping Skillsets in the Age of Analytics

Automation and greater involvement by business managers with the analytics team are just a couple of the changes that are in store for data science.

Data analytics is entering a new era, propelled by two trends in data science. First, business leaders are more frequently being moved into data roles, fueling the emergence of citizen data scientists. Second, technologies are making certain data science tasks – particularly data mining – more efficient, freeing data scientists to focus on insights. As these two trends converge, data science teams need to reshape their skillsets to reach their full potential today.

Business users increasingly charged with analytics roles

While the majority of data science leaders have years of experience in analytics, math and statistics, I have been working with many companies that are placing people from the business side (like operations or sales) into insights leadership roles. Overall, this is a smart strategy, providing data teams with better direction as to what the business really needs. It also allows the business side to understand exactly how data analysis works. With this information, they can better understand which analysis requests are most time consuming and how jobs are prioritized. However, this convergence of teams requires a new approach to data analytics.

Communication is the most fundamental skill in analytics

It may sound simple, but communication is the key to making this convergence a success. If I had to choose the single most important skill for data leaders on my team, it would be strong communication. Upcoming data leaders need to have a deep understanding of the business goals and a good relationship with department leaders, and communication is the only way to achieve these objectives. Data science leaders that align their priorities with the eventual consumer of their insights – the business team – are seen as trusted partners. This gives them an edge in gaining a seat at the strategy table and securing funding for additional resources.

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Article Credit: IW

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How to make the most of your SAP licences

There is no point in paying for something you never use – or worse, using the wrong licence. Doing the bare minimum for SAP licence management is not enough

Many licence reports seem to be based on the basic consideration that “one installation equals one licence”, and in the case of desktop, on-site software, this may be true.

However, if the thoughts of an IT manager only range as far as this, their company will soon be in trouble. In-depth analysis of all licences is fundamental to licence management.

These are even more important in the case of as-a-service software. Here, companies have to put some more “skin in the game” when it comes to enforcing licensing due-diligence.

SAP requires customers to perform a yearly self-measurement using the SAP tools USMM and LAW. However, these tools are not designed to optimise your licence position; they simply measure what you currently have in your systems. Before using the SAP measurement tools, it makes sense to look at your user classification. Here, you can determine the licences of your users according to their usage.

There are a number of steps IT departments need to take to avoid making over-payments to SAP.

Only pay for what you use

First, never pass raw LAW (Licence Administration Workbench) reports to SAP in the hope that the software provider will optimise the findings for you.

LAW reports contain multiple usage records of many modules across a large enterprise resource planning (ERP) system. SAP will count each use of a module as a requirement for a separate licence. Be sure to optimise this before you hand over any data to SAP.

Clearly, it is good practice to make sure you only pay for licences for people who are employed at the company. You don’t pay wages for people who leave, so why continue to pay an SAP user licence fee?

A well-engaged joiners, movers and leavers process should help track licences against the employee lifecycle. Significantly, keeping track of staff should cover those people whose jobs change: people who roll off assignments that use SAP should have their licences recovered to a licence pool.

Again, it makes financial sense only to buy the products you use. In an SAP installation this means only using the licences you really need. It doesn’t make sense to throw out IT budget for bells and whistles modules.

When assessing licences, IT departments should be meticulous with the different use cases for SAP in the business. A typical use case may run as follows: “As a I want to be able to so that I can complete .”

Aligning the technology behind these use cases should help to flush out which SAP technologies are essential for business operations, rather than simply nice to have.

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Article Credit: CW

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SAP technologies for sustainable development

SAP believes in leading with purpose to help the world run better and improve people’s lives. Claus Andresen, President and Managing Director, SAP Southeast Asia, believes that today’s digital generation, as future leaders, can help advance the agenda to drive sustainable social outcomes. And to do this, they need to beequipped withrelevantdigital capabilities.

Young people of ASEAN, for example, need to understand how big data and analytics can help them uncover insights about issues within their respective communities and propose recommendations that can address these challenges.

To address this need, SAP launched a strategic collaboration with the ASEAN Foundation in 2017. The initiatives rolled out under the Memorandum of Understanding (MoU) are aimed at equipping ASEAN youths with the skills they need to tackle society’s problems and thrive in the digital economy; build the capacity of innovative social enterprises that put young people on the path to successful careers and build a skilled workforce for the IT sector with training and workforce development programmes.

One of the programmes which we introduced under this MoU is the ASEAN Data Science Explorers. The competition solicited data-driven insights and ideas on the most pressing social issues in the region. The data analytics competition not only taught youth essential digital skills in harnessing the power of data but also encouraged them to focus on issues in ASEAN across six UN SDGs, namely:  good health and well-being, quality education, gender equality, clean water and sanitation, decent work and economic growth, and sustainable cities and communities.

Data has become the new life force that drives the world today. Businesses have always leveraged their company or customer information to make better, smarter, real time, fact-based decisions – from developing a new product, moving into a new market or simply redefining an old process.

New technologies, an increasing number of connected devices, combined with better data collection tools and processes are leading to an exponential increase in the volume and types of data available.  And this includes data around social issues.

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Article Credit: MB

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