Part 2: Take your strategy from paper to pavement

Cesare Mainardi and Paul Leinwand

Far too many strategies fail when it comes time to bring them to life. In fact, more than two-thirds of executives say they don’t have what they need to execute their strategy. Find out how your company can avoid falling into the strategy-through-execution gap by asking 3 questions.

Watch this video to find out how you can build a practical strategy that works.

Part 1: Why strategy matters

Cesare Mainardi and Paul Leinwand

In turbulent times, your strategy matters more than ever. The world's greatest companies weather adversity and uncertainty much more adeptly by operating from their core strengths. A strategy built on these differentiating capabilities helps you outpace the competition, achieve faster growth, and earn the right to win.

Watch this video to find out how you can build the right strategy and turn turmoil into transformation.

What are the ground rules for data-driven marketing?

IAN MICHIELS 

The quickest way to make a CMO roll their eyes is to tell them they should be making more data-driven decisions. Of course we should, everyone knows that. Unfortunately there are a lot of 'buts' attached to making this a reality.

“But the data I need is fragmented throughout the organisation.”

“But I have no way of linking customer data across channels.”

“But we don’t have the analytical skills internally to analyse the data.”

“But I can’t trust available data.”

The list goes on. There are, however, marketing leaders among us who actually do a very good job at leveraging data to inform marketing decisions. The problem is, when we talk about Big Data and data-driven decisions for marketers, it tends to veer toward boil-the-ocean concepts that are too big and audacious for even the largest marketing teams and budgets to take on. So what’s the practical reality from CMOs who are successful at making consistent data-driven decisions? What does 'data-driven' mean in 2015?

Last year, Gleanster Research surveyed over 9,700 senior marketing professionals in companies of all sizes in Europe and the US. And while there are lots of things your organisation should be doing with customer data, not all of them are realistic. You need to devote limited resources, finite time, and tight budgets to leverage data-driven marketing decisions.

There are a handful of somewhat obvious rules and guidelines that successful data-driven marketers consistently follow. The one caveat here is that these things are somewhat difficult to quantify from a research perspective. They are derived from conversations, analysis, and hands-on experience. Consider these the soft skills you’ll need to stay out of the rat holes and maintain credibly as a marketing leader who values the numbers.

Data is everybody’s friend.

Every organisation is applying analytics to marketing decisions – meaning your colleagues and peers also want to be data-driven marketers. At times even the same data produces different perspectives from internal stakeholders. Everyone’s got data to support their decisions. It’s important to realise that there are no one-size-fits-all answers in analysing marketing data – but there are directional and discernible trends. Always test assumptions. There are no magic insights you can derive from any form of analysis, even if you pay statisticians boatloads of money. Test, validate, and test again. You don’t have all the answers, but rather a process for uncovering the most informed decision. What you bring to the equation that is unique is your interpretation of the data and the actions you recommend for marketing optimisation.

Everyone is risk averse.

Risk comes from not knowing what we are doing. For marketers there’s a risk in sticking your neck out there and analysing customer data. What if the data is inaccurate? What if you don’t have the full picture? Tenacity and perseverance in using data to inform marketing decisions pays off. You may not garner the credibility you want initially, but if you always return to the data, risk-averse leaders will gravitate toward your insights rather than to a peer who relies on anecdotal assumptions. When you analyse data, always try to remove the risk from the findings, dig a little deeper, test alternatives.

It’s not a 'Big Data' challenge.

Sure, there’s a ton of data on customers at every organisation. Your job in marketing is not to analyse all of it. It’s to prioritise decisions and figure out where the path of least resistance lies to improve conversion, save costs, save time, and increase revenue. Pick one or two duties in your job and fix something. Anything, big or little. The practical reality is that you don’t have to analyse big data in marketing. You have to pick small samples and populations of data that can inform one or more decisions. World hunger is solved one slice of bread at a time – and every slice makes a difference in the aggregate. Someday machine learning will help us uncover the gems in big data, but today you have to start somewhere, with currently available data, in areas where you can effect change.

Simplicity is the ultimate sophistication.

That’s actually a quote from Leonardo Da Vinci. Marketers are overworked and underpaid. You have regular duties and responsibilities in your job, and normally they don’t account for committing time to analysing data. So you need to look for leverage in how you commit time and resources. If you’re a senior leader, don’t waste your team’s time chasing questions that can’t be answered. Prioritise a few decisions that will make a difference for the organisation and consider that a huge win when they prove valuable.

Context begets analytics.

The challenge with data is analysis paralysis. You have to know when to stop digging and take action. Marketers’ unique skillset for the organization is their creativity and emotionally charged perspective on how to drive a visceral reaction from a target audience. Those skills come from having context about what drives your buyer – what makes them purchase, engage, share, and react. For marketers the insights in customer data usually aren’t black and white. It’s the interpretation of the data as much as the analytical process. Sometimes marketers sell themselves short because they aren’t statisticians or metric oriented. The truth is, the most skilled statistician probably can’t provide the context you can when looking at the same data. They can isolate correlations, but those just tell you where to dig further. Marketers are incredibly valuable because they can layer context over analysis, so be confident in the value you offer.

Frame the opportunity, not the problem.

Every organisation has challenges – especially with respect to analysis. According to Gleanster Research, 8 out of 10 CMOs at large enterprise organizations believe they could be doing a better job leveraging available data to inform marketing decisions. But your job when analysing data is ALWAYS to uncover the opportunity to make a better decision, improve process, or boost key performance indicators. Don’t waste time identifying the problems with the availably of data or the internal use of data. Stay focused on effecting changes with insights informed by data, and eventually you start to stand out as someone who knows how to dig into the data and act accordingly.

Act like a two-year-old from time to time.

No, don’t throw a tantrum. Ask why. Ask why a lot. Why helps delve into the heart of your analysis even after you think you have come to a conclusion. “Why don’t we look at…x?” “Why is this the ideal conclusion?” Why also gives marketers credibility because it’s an analytical question. All too often senior leaders default to “well I think...” and they may or may not have the right answer. But why is going to drive the entire organisation down a discovery path. “I think” closes it out and dictates a decision.

8 Core Principles of Blue Ocean Strategy

The fundamentals that will jump start your strategy development process

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W. Chan Kim and Renée Mauborgne

What is distinctive about blue ocean strategy as a theory? How is blue ocean strategy different from a classic differentiation strategy? Is it another form of low cost strategy? What’s the research process behind it? In the decade since Blue Ocean Strategy was first published, we’ve fielded thousands of such questions. Some executives want to understand how it addresses the issue of execution. Some ask what the strategy is based on. Others question whether the strategy will be effective in their industry. We heard certain questions again and again and, in response, have identified eight core principles. Here we outline the essence of blue ocean strategy.

It’s grounded in data

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Blue ocean strategy is based on a decade long study of more than 150 strategic moves spanning more than 30 industries over 100 years. Industries ranged from hotels, cinema, retail, airlines, energy, computers, broadcasting, and construction to automobiles and steel. We analyzed not only winning business players who created blue oceans but also their less successful competitors. We searched for convergence among the group that created blue oceans and within less successful players caught in the red ocean. We also searched for divergence across these two groups. In so doing, we tried to discover the common factors leading to the creation of blue oceans and the key differences separating those winners from the mere survivors and the losers adrift in the red ocean. As our database and research have continued to expand and grow over the last ten years since the first edition of our book was published, we have continued to observe similar patterns whether blue oceans were created in for-profit industries, non-profit organizations, or the public sector.

It pursues differentiation and low cost

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Blue ocean strategy is based on the simultaneous pursuit of differentiation and low cost. It is an “and-and,” not an “either-or” strategy. Conventional wisdom holds that companies can either create greater value for customers at a higher cost or create reasonable value at a lower cost. Here strategy is seen as making a choice between differentiation and low cost. In contrast, blue ocean strategy seeks to break the value-cost tradeoff by eliminating and reducing factors an industry competes on and raising and creating factors the industry has never offered. This is what we call value innovation.

Value innovation is distinctively different from the competitive strategic approach that takes an industry structure as given and seeks to build a defensible position within the existing industry order. The strategic logic of value innovation guides companies to identify what buyers commonly value across the conventional boundaries of competition and reconstruct key factors across market boundaries, thereby achieving both differentiation and low cost and creating a leap in value for both buyers and the company.

It creates uncontested market space

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Blue ocean strategy doesn’t aim to out-perform the competition. It aims to make the competition irrelevant by reconstructing industry boundaries. Whereas conventional strategic approaches drive companies to define their industry similarly and focus on being the best within it, blue ocean strategy prompts them to break out of the accepted boundaries that define how they compete. Instead of looking within these boundaries, managers need to look systematically across them to create blue oceans – new and uncontested market space of new demand and high profitable growth.

It empowers you through tools and frameworks

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Blue ocean strategy offers systematic tools and frameworks to break away from the competition and create a blue ocean of uncontested market space. The field of strategy, by contrast, has predominantly focused on how to compete in established markets, creating an arsenal of analytic tools and frameworks to skillfully achieve this. Blue ocean strategy is built on the common strategic patterns behind the successful creation of blue oceans. These patterns have allowed us to develop underlying analytic frameworks, tools and methodologies to systematically link innovation to value and reconstruct industry boundaries. The visual and actionable frameworks and tools like the strategy canvas, four actions framework and six paths form the analytic foundations of the blue ocean creation process, bringing structure to what has historically been an unstructured problem in strategy. They provide a roadmap and critical visual guidance for systematically pursuing value innovation and creating uncontested market space. Companies can make proactive changes in industry or market fundamentals through the purposeful application of these blue ocean tools and frameworks.

It provides a step-by-step process

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From assessing the current state of play in an industry, to exploring the six paths to new market space, to understanding how to convert noncustomers into customers, blue ocean strategy provides a clear four-step process to break away from the competition and create a blue ocean of strong profitable growth. The four-step process is designed around the concepts and analytic tools of blue ocean strategy and fair process. It is built based on our strategy practices in the field with many companies over the last two decades. It allows managers and their teams to develop rigorous and concrete strategies while capturing the big picture. In this way, it presents an alternative to the existing strategic planning process, which is often criticized as a number-crunching exercise that keeps companies locked into making incremental improvements.

It maximizes opportunity while minimizing risk

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Blue ocean strategy is an opportunity-maximizing risk-minimizing strategy. Of course any strategy will always involve risks – be it red or blue. However, blue ocean strategy provides a robust mechanism to mitigate risks and increase the odds of success. A key framework here is the Blue Ocean Idea Index. The Blue Ocean Idea Index lets you test the commercial viability of your blue ocean ideas and shows you how to refine your ideas to maximize your upside while minimizing downside risks. It allows you to answer four key questions: First, is there a compelling reason for people to buy your offering? Second, is your offering priced to attract the mass of target buyers so they have a compelling ability to pay for it? Third, can you produce your offering at the strategic price and still earn a healthy profit from it? And finally what are the adoption hurdles in rolling out your idea and have you addressed these upfront? The first two questions address the revenue side of your business model. They ensure that you create a leap in net buyer value. The third question ensures the profit side of your business model. And the last question ensures that you have given good thought and addressed externalities that could trip up even the best new idea.

It builds execution into strategy

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The process and tools of blue ocean strategy are inclusive, easy to understand and communicate, and visual – all of which makes the process non-intimidating and an effective path to building execution into strategy and the collective wisdom of a company.
Equally as important, blue ocean strategy is a strategy that expressly joins analytics with the human dimension of organizations. It recognizes and pays respect to the importance of aligning people’s minds and hearts with a new strategy so that at the level of the individual, people embrace it of their own accord and willingly go beyond compulsory execution to voluntary cooperation in carrying it out. To achieve this, blue ocean strategy does not separate strategy formulation from execution. Although this disconnect may be a hallmark of most companies’ practices, our research shows it is also a hallmark of slow and questionable implementation and mechanical follow-through at best. Instead, blue ocean strategy builds execution into strategy from the start through the practice of fair process in the making and rolling out of strategy.

Fair Process, namely, engagement, explanation and expectation clarity, prepares the ground for implementation by invoking the most fundamental basis of action: trust, commitment, and the voluntary cooperation of people deep in an organization. Commitment, trust, and voluntary cooperation are not merely attitudes or behaviors. They are intangible capital. They allow companies to stand apart in the speed, quality, and consistency of their execution and to implement strategic shifts fast at low cost.

It shows you how to create a win-win outcome

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With its integrated approach, blue ocean strategy shows how to align the three strategy propositions – value, profit, and people – to ensure your organization is aligned around your new strategy and that it creates a win for buyers, the company, and for employees and stakeholders. For any strategy to be successful and sustainable an organization must develop an offering that attracts buyers; it must create a business model that enables the company to make a tidy profit; and it must motivate the people working for or with the company to execute the strategy. While good strategy content hinges upon a compelling value proposition for buyers and a robust profit proposition for the organization, sustainable strategy execution is based largely on a motivating people proposition. The alignment of the three propositions proposed by blue ocean strategy ensures that an organization is taking a holistic approach to the formulation and execution of strategy. Together the three propositions provide an organizing framework for creating a winning strategy that will benefit buyers, the company, as well as internal and external stakeholders.

http://www.blueoceanstrategy.com/

Building your roadmap for data-driven marketing

NEIL DAVEY
EditorMyCustomer.com

While the attraction of data-driven marketing isn’t in doubt, the challenge confronting businesses can be daunting.

According to the Q1 2014 Gleanster Research customer experience survey, about eight out of ten senior marketers believe their organisation could be doing a better job of using customer data to inform customer acquisition and retention strategies.

But with data-driven marketing involving so many working parts, the end goal can appear unobtainable.

To demonstrate the scale of the project, Adam Sharp, co-founder of CleverTouch and member of IDM’s Executive Council, highlights just some of the main characteristics of a data-driven organisation:

• They have a handle on their customers and prospect data and know the health of it.
• They have it in the one place (a data warehouse) that is linked to both their marketing automation and their CRM. At a minimum their CRM and marketing automation are linked and data is flowing between them.
• They look at client and prospect data not just titles, company size and location, but by profile, interest and degree of engagement – prospect, suspect, customer, advocate.
• They have moved away from ROI (which is reverse engineering their contribution) and are able to measure marketing activity and customer and prospect behaviours in such a way as to forecast the future impact on the business. 
• They have removed silos from within the organisation.
• They have enhanced workflows and realigned incentives to encourage data sharing.

It is therefore unsurprising that the task can appear daunting.

However, organisations must remember that data-driven marketing isn’t so much a destination as it is a transformational journey.  

So with this in mind, what are the key steps that organisations need to take on this journey towards being a data-driven organisation?

Implement an organisation-wide data strategy

Marketers have been making significant progress with the status of their data, and statistics from the Teradata 2015 Global Data-Driven Marketing Survey indicate that today data-driven marketing is either embedded or strategic for 78% of marketers – a large increase from only a year ago, when an ad hoc approach prevailed.

However, to be truly data-driven, data must be shared between business units, and for this to be successful, data needs to be managed consistently across the entire business. For this reason, businesses need to ensure that a strategic approach to data is adopted organisation-wide.

“An overall data strategy is vital and must be understood, adopted and rolled out across the business,” notes Daniel Telling, commercial director at Occam. “This needs to be reviewed on a consistent basis to ensure that all opportunities to capture useful and relevant information are exploited.”

Key points that need to be addressed include achieving consistency in how data is collected, catalogued, stored and used.

A data governance structure also needs to be established. Former D&B global chief data, insight and analytic officer Paul Ballew, recommends: “Invest the time upfront to bring your data and third party assets together in a systematic way, such as establishing a common entity identifier, nomenclature and taxonomy.”

Restructure the organisation

For data-driven marketing to become a reality, different business units and departments must be able to collaborate and share data. And as well as demanding that there is consistency in data management, this also means that organisations silos need to be broken down, both within the marketing department and throughout the entire business.

Indeed, structural silos represent a significant obstacle that prevents the successful sharing of data and inter-company collaboration. The Global Data-Driven Marketing Survey, for instance, indicates that internal silos prevent 42% of marketers from having such a full and consistent view of their customers.

In particular, silos must be broken down between IT and marketing. IT is a vital partner for the marketing department, playing a crucial role in connecting the touchpoints throughout the business, and thereby supporting data collection and integration. Survey findings indicate that over three-quarters of marketers view the development of a strategic partnership with IT as a priority.

“In terms of data-driven marketing, IT and marketing and sales work together best when silos are broken down at all levels and they are free to operate collegiately to adopt new technologies,” agrees Telling.

Create a cross-functional team

To support collaboration and break down silos, organisations should also develop a cross-functional team, including marketers and IT.

Katharine Hulls, VP marketing at Celebrus Technologies, notes: “Data and technology are just the start. To drive value from these investments requires the right skill-sets to analyse the data to deliver insight and drive action. To be truly successful it is important to create a cross-functional team, including marketers, analysts and IT as each brings their own skills, perspectives and experiences to deliver the best results.

“Forrester Research estimates that over 45% of Big Data deployments are for marketing – but that doesn’t mean that marketing should own marketing data and technology single-handedly: they must also recognise the skills IT brings to big data technology choices and deployment. It is therefore important for the CMO and CIO to work together, leverage different areas of expertise, pool resources and ensure the robust, scalable platforms are in place to deliver long-term value.”

Integrate data

Marketers need to create a single, complete, actionable and flexible view of their customers and prospects. However, over time, most enterprises have invested in numerous marketing technologies that specialises in different disciplines, leading to siloed data and a lack of visibility of prospect behaviour, and a lack of a holistic understanding of customers.

Telling says: “There are of course some physical barriers. With complex infrastructures, and the ballooning amount of interaction points businesses have with customers, it can be difficult to create a single point of truth. For years, organisations have been trying to create the single customer view so that interactions can be personal and informed for the benefit of both business and customer.”

To address this, enterprises will inevitably need to integrate customer data from disparate systems. Ian Michiels, principal & CEO at Gleanster Research, believes there are two avenues that organisations can take.

“Consider layering in a centralised platform that can pull in available customer data and unify it against individual customer records (and keep existing legacy technologies). Or consider replacing legacy tools with a multichannel platform that can centralise and simplify access to customer data that can be used in customer communications, inform customer channel preferences, and orchestrate a consistent customer experience.”

The Global Data-Driven Marketing Survey indicates that businesses are making progress with this challenge, with 43% of executives reporting they have achieved fully integrated data across teams, compared with only 18% in 2013.

Additionally, Michiels recommends augmenting customer data records with third-party data, highlighting that top-performing businesses are twice as likely as laggards to purchase additional data on existing customers from third-party providers. 

He notes: “Additional data attributes of existing customer data may provide insight into what your customers really look like so you can focus customer acquisition efforts toward more relevant target audiences. Things like household income, marital status, number of children, and other key attributes may not exist internally from existing customer interactions but can be acquired with reasonable accuracy, making it worthwhile for informing marketing spend.”

Leverage analytics

With the data integrated and augmented, businesses can utilise analytics to deliver actionable insights and guide decision-makers. And it is not just marketers that can benefit from this rigorous exercise – departments ranging from sales and customer service, to finance and purchasing, can all profit from greater insight into prospects and customers.

Hulls notes: “To date, relatively few organisations have extended their use of analytics beyond web analytics into areas such as journey mapping, golden pathing and affinities analysis. Those companies that have pushed on with analytics are reaping the rewards: research suggests that almost three quarters (71%) have achieved better customer targeting, 58% improved conversion, 51% improved marketing personalisation and 51% improved customer experience.

“Analytics tools provide marketers with the chance to find new insight, including individual customer journey analytics and marketing attribution. To make the most of these tools, marketers need to get stuck in; ask questions of the data and gain real confidence in the depth of customer insight now available.”

To drive results, Michiels recommends identifying high-priority customer personas (according to profitability or other goals), and then focusing analytics on those core personas and optimising for 3-5 of them.

Final points

Undertaking a project of such enormity can be daunting for the organisation, and can also be unsettling for the staff. It is important that businesses manage the change appropriately.

“One major obstacle across every organisation is the fear of change,” says Telling. “Organisations need fearless, brave people who are prepared to instigate the first steps. They may already exist in an organisation but are just not getting heard, or it may be down to you to discover them.”

He adds: “Businesses need to ensure that they are investing in people (training, skills and development), planning (strategy, comms and brand), and that the processes required to apply this to the marketing programme are in place to drive value across the entire organisation.”

“Make sure you have considered your current marketing model, how it will change and what the target operating model should be. For example, this can be change in terms of people and processes. Make changes across the entire organisation’s focus, and involve different parts of the business, communicating with them as much as possible. Access to the right data and technology is a great start, but useless without the ability to draw true value and insights from them.”

How to build a data-driven marketing strategy

CHRIS WARD
Deputy Editor of MyCustomer.com Sift

Having a data strategy is by no means a new discipline for marketers. Even back in the 1960s, pioneers such as Robert Kestnbaum were outlining new and imaginative ways to collect and analyse customer data to deliver more relevant marketing campaigns.

But while database marketing was for so long seen as a specific type of marketing in the subsequent years that followed Kestnbaums’ innovative work, the relatively recent advent of Big Data means that data analysis is now no longer just viewed as critical to one marketing function, but every marketing function.

American professor of psychology Dan Ariely famously described Big Data as being “like teenage sex – everyone talks about it, nobody really knows how to do it, everyone thinks everyone else is doing it, so everyone claims they are doing it” - a statement germane to what marketers were experiencing in the 2000s, when consumer data levels first truly exploded. However, in the last five years a seismic shift has occurred that makes this less and less representative.

Marketing is now predominantly a data science operation, and what’s more, the technology is there to assist this – a fact that consumers are well aware of. 100% of marketers state that successful brands must use customer data to drive marketing decisions, while IBM research shows that 75% of consumers now “expect organisations to understand their individual needs”. Brands are constantly referred to the need to turn their marketing operations from art to science. Subsequently, marketers must have a robust data-driven marketing strategy in place to ensure they not only capitalise on the Big Data opportunities, but also satisfy customer requirements that are frequently being made a larger part of their remit.

Strategic importance

A key factor driving this need is customer engagement. A 2014 study from Yankee Group found 64% of consumers said they needed to be connected to the internet at all times, a number that is rapidly increasing as more devices surface. With a separate study from Shopper Sciences stating the average number of sources of information people use to make a purchasing decision through their customer journey is up from 5.3 in 2010 to 10.4 in 2014, using data to understand when and what to target and engage prospective customers with is becoming more vital. It’s the combination of being proactive and reactive.  

“Businesses and brands must be able to engage effectively with customers to market successfully to them.  This may seem obvious, but harnessing rich customer data and using it to drive a marketing strategy is the best, if not, the only way to do this well,” says Jason Lark, managing director at Celerity Information Services.

“A purely reactive marketing approach is not enough. Cultivating great customer relationships takes time and planning and rich data is a key component. Data enables you to reach out to your customers in a targeted and meaningful manner, ensuring that the age-old marketing adage is fulfilled – allowing you to get the right message to the right people at the right time.”

And Kate Cooper, CEO of Bloom Worldwide agrees, stating that marketing without a data strategy is now too hazardous for targeting the modern-day consumer:

“Tactical marketing carries risk – it’s short-term and there’s no guarantee on results. However, a data-driven marketing strategy is formed by data such as sales stats, audience profile segments, customer loyalty, competitor performance and previous marketing campaign stats which allows businesses to base their strategy on what is really needed for both the customer and the business, rather than simply relying on guesswork/short-term fixes.”

However, such strategies are not commonplace. As Axel Schaefer, senior manager, strategic marketing EMEA at Adobe Systems, notes: “Today’s marketing leaders are expected to strategically use data, and activating programs based in the insights derived from what customer or visitors share with them. Although there is plenty of data available (data on customers, prospects, competitors, product lines, and others), very few marketing organisations truly understand what to do with it.”

So how can you build a data-driven marketing strategy?

Determine how data-driven you are as an organisation at present

As a first step on the way, companies should conduct a self-assessment in order to define the status quo.

Schaefer explains: “It’s essential to identify the areas of strength and those where your organisation needs to put more focus in order to achieve a sustainable organisation. Examples could be getting aware of the available data sources, understanding the goal setting across channels that may lead to common strategic goals, etc.

“As an organisation that wants to execute on data-driven marketing, all involved need to be very aware of the available resources, the restraints, requirements and needs, in order to develop actionable steps to a data-driven strategy roadmap.”

Determine what drives your decision-making

“Before any data can be collected, before any analysis can begin, and before any results can be sought you must first decide what the key driving factor is for any decisions you make,” advises Kentico’s Stephen Griffin.

What are your KPIs? Are you solely looking at revenue or income? Do you want to create an exceptional customer experience for your current customers? Are you only interested in attracting new customers or would you like to re-engage with old ones? Knowing what you really want to achieve sets you on your way to finding out how to achieve it.

Establish what data you need to collect to support your decision-making process

“Collecting the right data is what could make or break the entire process,” notes Griffin. “Having the wrong data will send you spinning into markets you just can’t handle or will just leave you scratching your head about where to go next.”

Divide your search criteria into quantitative (what happened? – number of site visits, number of downloads, etc.) and qualitative (why it happened? – customised landing page, customer specific offers, etc.).

There is a myriad of information that can be collected. You need to decide if you want information on a person’s buying habits, what pages they like to visit, what do they interact with most, etc., or their personal info such as email, address, age, etc.

Griffin continues: “Decide on the right info to give you the correct view of the customer to allow your decision making to become simpler.”

Collect the data

Determining how to get data in a nonintrusive manner should be a marketer’s first objective, because while a glut of customer data may be available to marketers, consumers are becoming less patient with brands that encroach on privacy, and have more power to cut brands loose when they do overstep the mark.

According to findings from the Aimia Institute, the data company that oversees customer loyalty schemes including Sainsbury’s Nectar card, over half (57%) of consumers are already taking steps to actively avoid companies, with a variety of methods including unfollowing brands on social channels (69%), closing accounts and subscriptions because individuals don't like the communications they are receiving (69%) and opting out from the majority of company email communications (58%).

Part of a marketer’s data collection remit must be to identify what data can be collected from first and third party sources without disrupting a positive customer experience. Only then can marketers start asking the following questions in the data collection process:

• Are we going to use contact information forms on your website?
• Will we have surveys available at certain touchpoints on the customer journey?
• Do we require the collection of geographical locations based on IP addresses?
• Does the number of page visits on the “About Us” page of our site have a bearing on buying habits, and if so do we collect that information?
• Do we have club membership forms?
• Are we carrying out in-store surveys?

This particular step “should also be a continuous one even as you move through the entire process”, says Griffin. The moments evolve. Buying habits differ, new trends emerge, technology advances, and people change. It is important for data collection points to remain open to change.

Analyse the data and create buyer personas

The key aim of data collection is to glean a detailed level of insight that will drive future marketing campaigns. “Data alone is not going to form the best marketing strategy,” says Kate Cooper. “Data driven marketing requires a top layer to be added. Insight. This is when the marketing team uses the data analysed to form a hypothesis, vision and ongoing strategy.

One core objective for many marketers is to develop buying personas from the data, with the Holy Grail being to create a single customer view (SCV), based on what information is gleaned about who each customer is, what they like to search, what they like to buy, what interests them and what influences them.

“All of this accumulated, highly valuable qualitative data must be well managed, and scored and used to inform a single customer view (SCV),” says Jason Lark. “Information can be scored on the importance and relevancy of different attributes and then used to inform the marketing strategy – how you will use this knowledge to reach your end goals. For example, this might help you make decisions as to what technologies can be used to support this process.”

Roll out your customer-focused information

With the groundwork done, you should now know what you’re trying to achieve, collected the data that is needed to achieve it and conducted analysis on it to find insights and build personas. Now it is time to build your content around your personas and put the right information in front of the right people at the right time.

Griffin says: “You want to ‘WOW’ your customers with how well you know them and delight them with the fantastic ‘personal’ offers you have for them. Show them new items and trends that match their persona that they may never have seen without you. In every channel and through all stages of the buying process, provide an experience akin to a personal shopper in a top boutique and keep your customer coming back for more.”

It is also at this point that marketers are able to incorporate technology such as marketing automation to ensure their content is also highly personalised. And while this might be the point that makes a data marketing campaign most susceptible to customers potentially opting-out of communications as mentioned earlier, it is also becoming increasingly expected among certain sections of technology-savvy consumer.

According to a survey from 3radical, 45% of consumers state they are unlikely to buy or engage with brands if they don’t make things relevant and personalised. And 30% of consumers say they will simply ignore communications from even their favourite brands if the marketing isn’t bespoke and targeted, even potentially leading to them ending a brand relationship altogether. Only with a robust data marketing strategy can these elements be achieved.

Measure ROI

Measuring ROI provides marketers with an opportunity to assess where analysis and insight is leading to a genuine return, but is often the hardest thing to monitor, as the statistic from a recent Kentico survey which states that only 17% online marketers constantly measure effectiveness, clearly highlights.  

You need to highlight the importance of the marketing team in the overall business value. Use the answers you generated when you determining what drives your decision-making, and use data to show the influence the process has had. Do you now have more customers? Are older customers returning? Have page visits or downloads increased on your site? All these things can point towards a successful data-driven strategy helping to improve the business value.

Repeat and improve

Remember: the process should be ongoing. As Schaefer notes: “Data-driven marketing needs to be a continuous and sustainable effort.”