OVERRELIANCE ON DATA-DRIVEN MARKETING

  • Category:
    Marketing
  • Document type:
    Essay
  • Level:
    Undergraduate
  • Page:
    5
  • Words:
    3309

Overreliance on Data-Driven Marketing

Contents

2Executive Summary

3Introduction

4Pros of Data-Driven Marketing

4Marketing Attribution

4Personalization

4Sales Funnel Visibility

5Pre-targeting

5Strategic Insight

5Setbacks of Over-Reliance on Data

6Creativity at a Threat

7More Challenges of Data-Driven Campaigns

8Recommendations

8Outside the Box Offense

9Blending Data with Creativity

10The Intelligence Brand Framework

13References

Executive Summary

In this digital era, the marketing field has evolved where marketers have been able to access huge data to conduct market analyses on customer trends as well as get insights on the performance of a brand in various markets. Industries that pioneered big data have reaped substantial benefits via increased sales and wide coverage through advertising. In spite of the benefits realized by use of big data in marketing, there has existed a big struggle between overreliance on big data and creativity. This paper examines the effects of overreliance on big data, citing the pros and cons of big data. The paper gives detailed analyses of what marketers miss when they solely rely on big data in their analyses, giving a plausible solution to the threat posed by this overreliance.

To begin with, this paper explores some of the benefits realized through data-driven marketing. Such benefits include marketing attribution, personalization of marketing messages, sales funnel visibility, pre-targeting and strategic insight. Further, this paper explores the frequently highlighted contentions against data obsession by marketers. The major cons of overreliance on big data by marketers include disregarding creativity which is a core driver in marketing success as it enables marketers to understand what prompts customers to behave in a given way. Creativity offers a humanistic experience with the customers, giving marketers insights on how to use the data they have to the success of the marketing process. Other cons of overreliance on data include lack of information, difficulty to extract data from different systems and issues with completeness and accuracy of data.

Finally, this paper gives a set of recommendations that marketers should employ to realize an effective marketing experience in this data-driven era. In order to realize a holistic experience in marketing, marketers should employ outside the box offense where they choose the most plausible option according to circumstances, blending data with creativity and employing the Intelligence Brand Framework to find a balance in marketing strategies.

Introduction

To most marketers, access to big data has become instrumental in achieving various goals such as market analysis and brand promotion. Data-driven marketing entails the practice of employing market data to achieve the goals of marketing enabling the quantitative measurement of results via the engagements of customers ultimately translating to greater value for the business (Blattberg, Glazer & Little, 2012). According to marketers, information about customer trends, patterns, their interactions with the sales process and social media activity is readily available and accessible. Marketers assert that this data has enabled them to utilize customer behavior to develop focused campaigns. Additionally, marketers feel that availability of data enhances the measurability as well as the effectiveness of the marketing campaigns. Despite these benefits, most marketers have solely depended on data-driven marketing, giving no room for creativity which has eroded the humanistic aspect of marketing. This paper will thus explore the effects of overreliance on data driven marketing, citing plausible recommendations to blend both creativity and data driven methods to achieve a holistic experience in marketing (Postma, 2012). According to most of these marketers, there are several advantages tied to data-driven marketing.

Pros of Data-Driven Marketing

Marketing Attribution

A variety of technological advancements has given marketers the opportunity to attribute various leads and conversations to a variety of advertising channels. Such technology includes call tracking that enables the marketer to identify locations with the highest concentration of their clients. Eventually, marketers use this information to optimize campaigns, and ultimately this enhances Return of Investment (Jeffery, 2010).

Personalization

Ability to access big data coupled with advanced analytics have enabled marketers to conduct highly targeted campaigns that encompass personalized messages. Studies indicate the possibility to deliver more than five times the ROI on marketing when businesses employ data-driven personalization. Additionally, marketers deliver their brand’s promotion messages at optimal times when they apply the advanced technologies (Jeffery, 2010).. With this kind of data, it is plausible to employ an in-depth insight to timeliness and relevancy to enhance the marketing campaign’s success as well as build on increased rate of consumer engagement.

Sales Funnel Visibility

Marketers use market data to identify the specific content moving customers down every stage of the sales chain. Such data is important in distinguishing the assets efficient for the company from those materials that are ineffective. Identification of the efficient assets translates to campaigns optimization where the content that resonates with the marketer’s prospects is used ultimately compelling faster and consistent movement of the products through the sales funnel (Jeffery, 2010)..

Pre-targeting

Pre-targeting involves the idea of using big data for the prediction of customer’s preferences hence messages are tailor made to align to the needs of the customers. Then this data is accessed during the buying phase, where it has a fundamental role in enhancing the effectiveness of messages received by the customers (Jeffery, 2010).. Pre-targeting further can be viewed as a way of meeting the customer’s needs by what they would do and not on the basis of what they already have done. Through pre-targeting, marketers are able to connect effectively with prospects in the right timing thus the messages sent to the customers is always relevant.

Strategic Insight

One of the core benefits associated with advanced analytics is enhancing access to huge data and most importantly the right data. Further, advanced analytic enhances the understanding of the best ways of applying this data in marketing. Marketers are able to conduct campaign employing strategic precision since they are able to gain actionable insight through the use of premium tools of advanced analytics. In most cases, marketers use the wealth of social media consumer information consistently to shape their marketing decisions as well as fulfill conversion and lead generation goals (Jeffery, 2010). Ideally, marketers apply this data in a variety of marketing processes in the creation of increasingly targeted campaigns to realize heightened impacts in their sales.

Setbacks of Over-Reliance on Data

In spite of the benefits that big data presents, overreliance presents have some inherent risks. It is plausible for marketers to realize that data alone is not the key driver of business growth. Although data plays an integral role in bringing precision to executing various market targeted strategies, it does not contribute in any way towards motivation or creation of desire for customers to transact with the company. Although data enhances a deeper understanding of the customers, it is primarily the content that stirs an emotional connection between the client, the marketer and the product. It is thus believed that today’s marketers are at a risk of cultivating half a brain through their over-reliance on data only. Marketers need to understand that the intersection of head and heart is where true brand intelligence lives. At this intersection, the emotional self is seen meeting with the analytical self (Sorofman & Frank, 2014). Some of the disconnects that are realized by overreliance in data-driven marketing include

Creativity at a Threat

The increasing rise of programmatic buying, as well as overreliance in performance data and analytics by marketers, has transformed the marketing scope into a numbers game. Creativity entails the defeat of habit via a focus on originality, and it cannot be achieved via data analyses. In creativity, individuals express original ideas which bring s value since we are able to connect with the people who later become customers. Overreliance on data analyses makes marketers miss out on special interesting insights about the customers (Blattberg, Kim, & Neslin, 2008).

Senior executives are overly addicted to numbers to analyze what works with no or little concern on why consumers engage. Data-driven marketing does not establish truly what motivates the customer hence in one or another diminishes the brand’s identity. Through creativity marketing, marketers should be able to play into popular culture, enabling them to break through the clutter. Marketers over-concentrate on optimization, overlooking creative considerations as well as ideas capable of realizing serious returns on investment. Time spent on data analyses only yields results that help in describing what people actually do but do not give insights into why people do it. Most brands are seen shifting from their creative offensive ultimately neglecting consumer engagement.

Companies are more likely to enhance revenue growth of up to more than ten percent when they foster creativity when compared to their peer companies. Additionally, marketers at times fail to take the overall company into consideration when they base their strategic decisions on just satisfying particular metrics. Such a case happens when marketers are overly concerned with achieving their metric goals, overlooking their role in achieving the company goals together with other teams. When other teams seem to be stuck, these metric obsessed marketers seem not to be interested in giving a hand since they find it as inefficient use of their time. Such thoughts ruin accountability of marketers as well their sense of teamwork.

More Challenges of Data-Driven Campaigns

Apparently, we find that data-driven marketing has a major challenge, which is based on inadequate information that pertains to the attitudes and perceptions of the customers. This fact makes data-driven methods analyze only past customers and current customers with no strategy to impact on prospective customers

Further, data driven marketing has issues related to difficulty to extract data from different systems. Various institutions have a tendency of storing data in multiple disparate systems. When data is widely spread in a variety of systems, it becomes highly challenging to link all the information that relate to a single consumer together.

Additionallyin most instances, data is always incomplete and in other cases, it is possible to obtain inaccurate data. This is true for huge organizations which serve a huge customer base such as in a call center or Facebook (Burby & Atchison, 2007). In such cases basing one’s arguments on insights driven by likes on a given product may be misleading since various social media people can like a product even without reading or knowing how it is used. In the case of a large call center, even if the company employs the best training as well as the use of the most effective computer software, there is a high probability that some information will be missing. Some of the information being entered in wrong fields, some data mistyped among other mistakes associated with data collection. Such issues call for the employment of substantial effort to conduct a data cleaning exercise before any data analyses can be carried out. Due to difficulties in cleaning data, some of the records may be eventually discarded while in other areas some records may be allocated default values.

Recommendations

Various approaches are employed to help researchers deal with missing data. Such approaches include searching for data in outside sources such as those in census data. Another way researchers try to compensate for missing data is through estimation of value from the aggregated data. Such approaches may give a plausible insight while in another case may be misleading. To avoid this mistakes in marketing is always advisable to blend both data methods with actual market research methods where research have a personal experience with the customers to understand why they behave in a given way as well as understand their expectations on various brands (Ryan & Jones, 2009).

Outside the Box Offense

In essence, marketers need to understand that a big picture perspective is what most of the brand’s offensive strategy should begin with a substantially strong creative idea. Reliance on this strong idea is driven by the marketer’s strong believes in the success of the idea hence acts as taking a leap of faith. Marketers who are obsessed with data appear less likely to bank on such ideas since they avoid taking such risks. Ideally, these marketers forget that some the most plausible concepts in marketing could not be validated using data before they were executed hence they solely depended on strong creative ideas.

A plausible example of out of the box offense can be attributed to the case of Avis Car Rental that experienced ten years of no profit. The company for these ten years had relied solely on data in annoying markets and trying to understand its customers. After the ten years, the company hired a new marketing manager Doyle Dane, who was to initiate a new brand campaign for the company. Doyle introduced a campaign based on a creative idea ‘we try harder” who rewards were experienced within a years’ time since the company started coming out of the red. In this case, if Avis had influenced Doyle’s plans and insisted that he focus his campaigns on the patterns proven by the data, the out of the box campaign would not have been introduced hence the company would still have followed the previous doctrine realize no change in its returns. Apparently it is true that most marketers bank on big data which is more familiar rather than depending on predictions in their campaigns since they are afraid of taking risks.

Blending Data with Creativity

In spite of the fact that creativity plays a major role in connecting and understanding why customers behave in a given way, data should not be totally ignored. Marketers who bank on employing creative ideas should understand that data plays an integral role in directing creativity. It helps marketers to maintain a balance between compelling execution and insight-driven ideas when they incorporate creativity and data means. Smart marketing managers are able to bring together both their creative teams and data geeks. Creative marketers such as designers in the marketing team should understand programmatics so that they will adequately be equipped in tailoring aesthetics as well as messaging to various audiences. Similarly, teams of programmatic analysts should also be prompted to be creative for them to be able to communicate insights from a variety of data.

It is plausible for marketers to understand that a campaign’s sales rely on creativity with over a half of its impact. Though a company may have the best data team and huge data to analyze its markets, it may eventually fail in its attempts to run effective campaigns if it lacks viable and creative ideas. Additionally, there is in no way that optimization will ever acquire a marketing award (Tapp, 2008). Marketers should, therefore, use data as a means of supplementing a creative idea or strategy rather than using data to substitute these creative strategies. Blending data means and creative means will eventually power a digital success in marketing.

The Intelligence Brand Framework

Apparently, Sorofman and Frank (2014) conducted research on various marketers to enable them to develop an intelligent brand network. This framework is used to provide a structure that can be used to thinking about creative marketing approaches via a combination of both data driven and humanistic methods. The goal of this structure is to ensure that markers strategically apply both methods in their operations and are not overly blinded by the application of only one method that can eventually result into unfavorable implication. Understanding of the tradeoff of these marketing approaches is crucial in realizing organization’s broader goals. The Intelligence Brand Framework is thus vital in helping marketers find a balance. The Intelligence Brand Framework has four major domains that make plausible in addressing the basic marketing competencies.

Firstly, there is Data-Centric domain where various data sources are integrated to yield patterns, help us make predictions, quantitatively and qualitatively measure results and finally enable the marketer to make the requisite correction of courses in a bid to optimize strategies. Secondly, there is Human-centric domain, where available data play an integral role. Otherwise, in the human-centric domain, patterns are discerned, as it primarily takes action based on human judgment, intellect, moments of inspiration as well as emotions (Sorofman & Frank, 2014).

Thirdly, there is Strategic domain which offers the marketers an opportunity to evaluate why and what to incorporate in their marketing process. Marketers employ a combination of human-centric and data-centric practices to reach to the most plausible ideas of marketing.

And fourthly, there is the Operational domain which primarily focuses of the “how” marketers will apply both human beings and automation to deliver the best experiences and offers to the right customer within the right time. Marketers’ goals under this domain are to optimize engagement as well the conversion rates (Sorofman & Frank, 2014).

Apparently, where these domains intersect, provide the most plausible point to gain the most plausible strategy to employ towards effective marketing. This point of intersection reveals strategic leverage points that represent the modern marketer’s advanced competencies. These leverage points include observation, engagement, inspiration and automation. Observation is a leverage point where marketers bank on customer behaviors to reveal new insights. Customer new insights in this context are found through employing traditional methods (Sorofman & Frank, 2014). Marketers focus on census data mining, surveys as well as new approaches such as text analysis and digital ethnography. Engagement, on the other hand, enshrines the process of making impersonal brand messages be perceived as genuine human dialogues. In a bid to humanize a brand, marketers usually engage in social interactions as a way of surprising and delighting customers. Inspiration as a leverage point encompasses the capturing, indexing and harvesting of the moments of human genius to gain a strategic advantage. In order to achieve inspiration, marketers employ the use of gamification, collaboration, crowdsourcing, and natural language processing in a bid to tap into human intelligence. Lastly, automation entails how machines allow marketers achieve higher precision levels through quick access to mass data. Marketers can therefore easily target offers and experiences across a variety of analytics and channels ultimately closing the loop that deter effectiveness in marketing.

According to Sorofman & Frank (2014), a company that strategically harnesses inspiration is IBM where it blends it with innovation jams, to gains the best ideas from crowdsourcing. P&G, on the other hand, employs the observation strategy via advanced ethnographic techniques and focus groups to aid in tuning into the customer’s voice. Further, we find an online retailer like Zappos employing automation to transform the knowledge off customers into personalized experiences that eventually translated to more sales as customers become attached to the brand. Engagements mainly focus on a company like REI, which is an outdoor retailer that strategically combines social listening with customer engagement to gain advocacy and loyalty in its brand path.

In conclusion, it is apparent that depending solely on big data to understand markets, analyze customer behaviors and devise marketing strategies is denying marketer the opportunity to gain insights on what motivates their customers as well as the customer’s wishes. To realize a holistic experience in marketing, it is plausible to adopt a mix of data-oriented or programmatic methods with creativity. Marketers should, therefore, use data as a means of supplementing a creative idea or strategy rather than using data to substitute these creative strategies. Blending data means and creative means will eventually power a digital success in marketing.

References

Blattberg, R. C., Glazer, R., & Little, J. D. (2012). The Marketing information revolution. Boston, MA: Harvard Business School Press.

Blattberg, R. C., Kim, P., & Neslin, S. A. (2008). Database marketing: Analyzing and managing customers. New York: Springer.

Burby, J., & Atchison, S. (2007). Actionable web analytics: Using data to make smart business decisions. Indianapolis, IN: Wiley Pub.

Jeffery, M. (2010). Data-driven marketing: The 15 metrics everyone in marketing should know. Hoboken, NJ: John Wiley.

Postma, P. (2012). The new marketing era: Marketing to the imagination in a technology-driven world. New York: McGraw-Hill.

Ryan, D., & Jones, C. (2009). Understanding digital marketing: Marketing strategies for engaging the digital generation. London: Kogan Page.

Sorofman, J., & Frank, A. (2014, February 25). What Data-Obsessed Marketers Don’t Understand. Retrieved May 13, 2016, from

https://hbr.org/2014/02/what-data-obsessed-marketers-dont-understand

Tapp, A. (2008). Principles of direct and database marketing: A digital orientation. Harlow: Financial Times Prentice Hall.