Marketing-analytics222.pdf

Literature Review The world is changing and changing fast. Technology, industry, education, health even eating habit also change. There is hardly anything in life that is not changing. Some change we like, while others create surprising factors. In recent years we see a transformation of marketing is underway as we spend more time on our mobiles, tablets and laptops. The challenge for brands is to connect with customers through all these devices in real time and create campaigns that work across social media, display advertising and e-commerce. On the other hand, Marketing Analytics (MA) is a relatively new but increasingly prominent field in which data tools are applied to quantify and monitor marketing performance and customer information to optimize investments in marketing programs and maximize customer interaction. In this literature there going to discuss about what is marketing analytics, main opportunities and challenges of marketing analysis and more importantly how it is changing in the marketing industry. Marketing Analytics is the process of using data collected from consumers and on consumers to perform analysis. Marketing analytics is used to make key marketing decisions, such as how much money to spend on advertising. (Ron Bermon, December, 2016). Marketing analytics (MA) professionals and organizations are currently tasked with generating intelligence to improve marketing performance, to create insights and knowledge for driving customer engagement, to measure customer lifetime value, and to help drive marketing performance by optimizing investments of marketing programs and maximizing customer interaction (Ramani and Kumar 2008). Davenport claimed that analytics itself is a management strategy requiring top management support and viewing analytics as a program where people skills, applied methodologies, and technologies matter in gaining firm-wide adoption (Davenport and Harris 2007). Successful organizations in the MA arena enjoy executive-level endorsement for the broad use of analytics to manage day-to-day operations and shape future strategies (Kiron et al. 2011). When executives foster analytics-driven decisions, then analytics champions are more likely to exist within organizations. Research suggests that a firm’s top management must not only commit adequate resources in the form of employee analytic skills, data, and IT, but it must also nurture a culture that supports the use of MA (Wedel and Kannan 2016). Such a culture can ensure that the insights gained from MA are efficiently deployed (Germann et al. 2013). Companies that are successful in adopting and deploying analytics tend to be more effective at driving the information transformation cycle including capturing, analyzing, aggregating, integrating, and disseminating information, and thus at embedding analytics in the organization (Kiron et al. 2011).

Analytics can also inform critical collaborative investment decisions. As a result, analytics is frequently used for strategic objectives aimed at increasing competitive advantage (Kiron et al. 2011). Digital Analytics is the analysis of qualitative and quantitative data to drive a continual improvement of the online experience that your customers & your potential customers have which translates to your desired outcomes both online & offline. (Avinash Kaushik, the author of Web analytics 2.0) Even though the term marketing analytics is not new, considering that the Nielsen rating originated in the 1920s, the digital explosion has also created a widespread interest in digital analytics, big data, and data mining (Petrescu and Krishen 2017). As conference panel discussions revealed, business schools are trying to determine where to place marketing analytics, since the field spans multiple departments and is interdisciplinary and inclusive in content (Krishen and Petrescu 2017). There are a few inputs and processes related to marketing analytics that can be clarified for the benefit of marketing academics, researchers, and practitioners. For example: What is marketing analytics and how does it relate to market strategy and marketing research and their management of data? Where the field of marketing analytics should be placed? Should we focus on breadth or depth in departing marketing analytics knowledge? How can marketing analytics researchers better cooperate and evolve with marketing practitioners? What are the actionable ways that marketing analytics provides mechanisms and processes which connect data, information, and knowledge? (Krishen and Petrescu 2018) There is a role followed in Marketing analytics named as 10/90 rule put forth by Avinesh Kaushik for magnificent web analytics success states, “If you have 100$ to spend on digital analytics, spend: -

10$ on tools 90$ on people

As tools and data become more affordable over time, your team remains vital.

Marketing analytics Marketing analytics (MA) basically refers to measuring, analyzing and optimizing the marketing performance of a campaign & customer information to optimize investments in marketing programs and maximize customer interaction. The purpose of marketing analytics is to maximize the effectiveness of a campaign and improve the return on investment. Marketing analytics refers to the data that enables modern marketers to optimize their campaign budgets and minimize resources wastage while creating maximum impact. On the other hand, marketing analytics takes on a wider perspective. It focuses on your marketing campaigns and activities, multichannel attribution, marketing mix modeling, distribution of marketing efforts and the like, all within the context of discovering ROI and how effective your marketing tactics and strategies are.

MA is a sub-discipline of broader analytics and includes the people, processes, and technology to generate insights that improve marketing performance. MA address top management concerns that may lead to a failure in allocating resources for marketing investments. Marketing analytics can also provide an assessment & accountability for marketing effectiveness. Marketing analytics tools track the behaviors of individuals within the product so that teams can monitor channel activity, tie activities back to revenue, gather insights, and test new ideas. It has become conventional wisdom about a company’s ability to generate intelligence continuously about customers’ expressed & latent needs, and how to satisfy those needs is essential to create superior customer value.

There are five types of tools used in marketing analytics which are playing an important role in driving superior industry growth.Marketing Dashboard tools Marketing Dashboard tools are used for data unification. To save time, companies often deploy marketing dashboard tools. Marketing dashboard tools like Mixpanel, Cife, and Klipfolio, as well as a variety of business intelligence (BI) tools, Telecommunication Industry In telecommunication industry companies offer many packages, services to their customers through their website and mobile apps. So among the marketing analytics tools event based tools monitor the performance of such campaigns over customers and testing tools measure the effectiveness and ROI from massaging in-app notification, e-mail notification. So we think among different industries in our country, if telecommunication industry use this two tools they can gain more success than the other industries. Both the tools, their usages, implications, opportunities and challenges are given below-

A) Usages of two tools 1. Event-based tools Event-based tools also known as click analysis. Event-based tools track the actions of individual users within a website, app, or platform. There are some event based tools like mix panel, heap analysis, oribi whose main goal is to track website one’s website or mobile app. So these tools can track, count and take effective action to provoke targeted customers of those mentioned industries. Usages Track the performance & behavior of the visitors, based on which segmentation can be made.     

Track any change automatically like how users interact with every feature Help increase user’s engagement & conversion rates from visitor to users, See from where visitors are coming, how they are referred to website, time spend on it. Can create customized reports that segments data by traffic source, geolocation, browsers & operating systems, Provide location based services and personalized advertising.

Testing tool Testing tools, sometimes simply referred to as A/B testing. A/B testing tools are available as- Standalone tools: Optimizely, VWO, - All-in-one analytics platform: Mixpanel. The three most common messaging channels for A/B testing tools are:   

Email or Push notifications In-app notifications SMS

Usages   

Allow teams to test multiple variants of a feature or message. Based on the test results, the team can learn what users like and can develop product thereby. Can test which marketing message convinces more users to make in-app purchases, or whether emails or push notifications are more effective at resurrecting churned users

B) Implications on industry So, by using event based tools companies can do the following thingsReal time analysis & - Control network dynamic congestion decision making - Data interactive exploration -location based services and personalized advertising. Precise marketing

- Offer optimization - Churn identification & prediction - Package design for specific over the top (OTT) Operation efficiency - Preemptive customers interactive voice response - Network ROI analysis intelligent network planning - Cell-site optimization Innovative business - Payment of data for increasing sales model -Match demand & offering nearby. Customer experience - Dynamic profiling & enhanced customer segmentation enhancement - Detailed weblog enquiry

C) Opportunity  As behaviors of visitors can be tracked by event based tools companies can segment & design different campaign or offerings customized to each segment. After that by measuring the effectiveness of campaign they can understand whether the desired demand is fulfilled or any other demand is created. That may create another opportunity to introduce new campaign or offerings. For example, telecom companies such as Robi axiata Ltd. are introducing new apps continuously based on customer needs mentioned in their websites by visitors like-

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- My Robi app for different internet packages - iFlix for entertainment - Robi shop for online smartphone devices Through controlling congestion & intelligent network planning, call drop is reduced. For this facility usage rate can be increased which may lead to higher profit to telco industry. Based on the information tracked, the top users can be encouraged by providing different offering like Banglalink named top user as gold user, platinum user against which the company provide internet packages & several offerings. So, by providing such offerings companies can provoke customers more usage & get more offerings.

So, by measuring the customer responses toward these apps, Robi can introduce new apps as the solution of further customer problems.

D) Challenges  There is a possibility that the cost required for arranging marketing analytics system may not be covered by the revenue or conversion rate generated from visitors to users.  As telecommunication industry is mostly service based, its effectiveness depends on employee responsible for operating analytics technologies. But in our country finding such skilled employee is difficult.  Up-to certain period the costs of analytics tools is more than the benefit coming from that technology. For example- Though the market leader somehow cover the initial cost but for the market follower or a startup company have to face difficulty to cover the cost.  Companies may have hunches, but until their ideas are verified as true or false, it’s difficult to know if feature changes actually improve the product or not. So they have to wait for the result that increase time and energy cost.

Automobile Industry The automotive industry is a growing market comprised of many subgroups which include: engineering, design, next generation manufacturing, distribution, and aftermarket. Automotive companies are focused on controlling cost, improving efficiency and utilization of alternative energy engines. Systems controlled by sensors have become integral in today’s automobiles, as a part of sensors visual behavior tools has made most electro-mechanical devices that better refined and more efficient with their application. The development and deployment of numerous visual behavior tools support and enable the introduction of advanced analytics systems, although there are challenges regarding robustness, reliability, quality and cost. New these tools are emerging to improve system functionality and to enable future advanced systems. Usages, implications, opportunity and challenges are given belowA) Usages of tools Visual behavior tools Visual behavior tools reveal where users spend time looking at the screen. They’re often compared to looking over users’ shoulders to see which content draws the most attention. It can rather be seen as an integral approach combining visualization, human factors and data analysis. Some of the most common visual analytics tools that highlights the most heavily trafficked or clicked areas. —HotJar, CrazyEgg, and Sumo. The visual analytics mantra: “Analyse First - Show the Important - Zoom, Filter and Analyse Further - Details on Demand” Usages  

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Using visual analytics provide deeper understanding of data & sense. Teams can use visual behavior data to rearrange their automobile’s interface and improve the service. Visual behavioral tools identify a variety of sensors to perceive their surroundings, such as radar, computer vision, Lidar, sonar, GPS, odometer and inertial measurement units. Though Advanced control this analytics tool systems interpret sensory information to identify appropriate navigation paths, as well as obstacles.

B) Implications  Due to deeper understanding companies can identify the latent demand of customers. By identifying demand of visitors companies can add new features into their automobiles that may fulfil their demand & can allure them from competitors.

C) Opportunities  Visualization is used as a means to efficiently communicate and explore the information space when automatic methods fail. So, it creates opportunity for automobile companies to keep more information on that space that may provide proper insight about the potential demand of customers. So from that companies can design new features that may attract more customers. D) Challenges  Visual analytics tools may overlook information among a large information space.  The eye-tracking or body posture that is tracked by visual analytics tool may not always the proper representation of human psychology. So, due to misunderstanding of such behavior wrong decision may be made by the authority. FMCG Industry Today, FMCG manufacturers rely on consumers ‘pulling’ products through the supply chain; thus, they require a better understanding of consumer behavior and choices. Consumers are well-informed about product information—in particular, promotions and price comparisons via the Internet—which makes predicting behavior very complex. This is where business analytics plays a very important role, as it allows organizations to derive predictive insights to enable competitive fact based decisions. Armed with deeper insights into consumer behavior, FMCG manufacturers will be able to direct R&D investment, improve the effectiveness of marketing and maximize supply chain efficiencies. Digital marketing analytics tools Digital marketing analytics tools collect data from marketing and advertising channels. They fall into five categories such as SEO, SEM, Social media platforms, Display ad platforms, and Predictive-scoring model platforms. Benefit criteria

Business challenges

Description Usage • Build a linear regression model to understand the impact of demand drivers on sales volume and calculate base volume.

Trade promotion optimization

• Identifying the proper price and discount point that • Calculate actual cost of promotions maximizes sales and return based on the individual components. on investment (ROI) • Calculate ROI for promotional events.

• Optimizing promotions to Implication improve sales performance of • Gain insights into the profitability of newly launched products promotions across stores, regions and products. • Enhance ability to benchmark scheme performance Usage

Help Marketing modelling

• Calculating ROI of • Develop a framework to show the advertisement spend across impact of various marketing campaigns various channels like on sales television, print and web in • Evaluate the effectiveness, ROI and mix • Understanding consumer simulate what-if scenarios behavior with regard to Implication exposure to advertising • Prioritize advertisement and promotion spent in favor of channels that provide better ROI • Reduce the total spending advertising and promotion Usage

on

• This tool uses Analytic hierarchy process (AHP) that is a prominent • Finding a vendor evaluation approach in solving multi-criterion method to facilitate an decision-making problems. objective, unbiased selection process • The method allows the incorporation of judgements on intangible qualitative • Identifying the key metrics criteria alongside tangible quantitative Improve vendor of vendor performance that criteria. selection model can help during negotiation with vendors on specific • Measure vendor performance among points peers and across time • Finding a robust framework Implication that can measure • Help avoiding conflicts through vendors’ performance collaborative decision making

• Generate a repeatable process that saves time Usage • Identifying a scientific • Develop a robust sales forecasting methodology to accurately model through aggregation and predict future sales volumes statistical analysis of data Help in Sales • Improving target market • Develop a structured what-if analysis forecasting setting by identifying current mechanism to create multiple scenarios market conditions and their impact on customer sales

Implication • Predict sales volumes based on critical demand drivers • Improve decision making through structured scenario analysis • Understanding the impact Usage on sales for a given change in price (pricing elasticity) • Build a pricing model to enable an across products and effective pricing policy for various understand the impact on the product categories contribution margin Help in Pricing • Optimize pricing to improve margins recommendation • Ensuring a consistent and bottom-line profitability scientific methodology is being applied to pricing Implication decisions across • Data-driven pricing suggestions for categories/outlets greater sales and incremental contribution margin

Usage • Capturing customer • Capture unstructured data across feedback across various various social media platforms through social media platforms and using web crawlers or web spider.

meaningful • A text mining model for parsing conversations into positive, neutral and negative buckets. • Improving brand strength and engage with customers in Implication a meaningful way • Sentiment analysis can help to track consumer behavior in real time across channels, monitor online brand health and also uncover the levers that can have a significant business impact. Usage derive conclusions

Sentiment analysis

Inventory optimization

Multichannel advertising analytics

•Employ statistical modelling techniques to perform inventory stock • Align inventory planning, level vs lost sales scenario analysis forecasting and execution capabilities across the •Develop robust demand forecasts organization through statistical analysis of data across outlets • Obtain insights from vast volumes of data at the stock Implication keeping unit (SKU) location on a weekly/daily level to • Suggest recommendations to reduce improve inventory out-of-stock frequency forecasting • Optimize balance between inventory stock and lost sales based on economics & competitive environment of the business. • Understanding which Usage combination of ad exposures interacts to influence the • Quantify the contribution of each consumer to make a purchase element of advertising For example: A TV ad can prompt a Google search on a mobile phone, which can lead to a click through on a display ad and ultimately end in sales.

• Real-time redistribution of resources across marketing activities according to optimization scenarios Implication

• Identifying whether the Measure how TV, print, radio and online company is investing the ads each functioned independently to right amount at the right point drive sales

in the customer decision journey to purchase a product Usage • Using modelling, PwC’s price and pack analytics optimizes channel • Defining the right brands, performance, package diversity, and packs and prices for the pricing and other key value drivers. Price and pack specified channel/customer to analytics meet targeted consumer and Implication shopper needs • Increase revenue across the portfolio • Increase market share and value share Usage

Vending machine ROI

Assortment intelligence

• Forecasting incremental • Identify true cost to serve of vending volume and contribution machine network, including both direct margin associated with new and indirect costs vending opportunities • Develop data-driven fact base for • Understanding ROI of precision price setting, with and without adding cashless swipe to new cashless swipe and existing machines, including both cost and Implication precision pricing • Profit drivers quantified (commission, location, cost to serve, etc.) • Tracking the competitors’ Usage assortments and their pricing dynamically (real time) to • Real-time price monitoring and optimize personal product analytics using advanced artificial intelligence (AI), semantic analysis, portfolio data mining, and image-recognition • Identifying products, brands algorithms and categories with • Trend analysis (trending now, popular) competitive advantages using predictive algorithms in order to • Identifying gaps in sell the right products at the right time catalogues so as to take and drop products that are cooling in decisions on adding them and popularity overlaps to price them at Implication extremely competitive rate

• Provide a view of competitors’ product assortments, enabling a company to quickly adjust its own product mix and pricing so as to make profitable pricing decisions and drive sales performance

Automotive Industry Dashboard tools provide unique solutions for automotive industry that struggle with the overbearing tasks of creating manual reports, report consolidation, analysis, and planning. This tool integrate with the most important data in Automotive Industry and securely store it in our data warehouse in the cloud. It doesn’t matter how many dealerships you have or even if they have different software providers. Reporting dashboards have long been used in business intelligence to summarize information into instantly digestible analytics that provide at-aglance visibility into business performance.

Marketing Dashboard Tools A dashboard report is a software application that is used to track and monitor the health of an organization or department by reporting on KPIs, business metrics, and analytics. Marketing dashboards are designed to provide teams with a real-time window into marketing performance. Marketing dashboards are marketing reports designed for continuous monitoring and a broad distribution. Like a car’s dashboard, a marketing dashboard allows the team to drive towards their goals with ready knowledge of what’s going on under the hood. This type of visibility enables course corrections on a daily, and even hourly, basis, in contrast to traditional monthly or quarterly reports.

Features of dashboards At the most basic level, business dashboards share certain common features. This section explores some of these features and their impact on dashboard project. Data visualizations: Selecting the right visualization for automotive industry is an important part of dashboard design. Data visualizations are graphical representations of data, and are used to simplify the transmission of sometimes complex information. Here's a short guide with some information about the most common types of data visualizations in dashboard design.

Tables

Line charts

Bar charts

Gauges

There are different type’s dashboard tools which are used in different industry sectors, likeAutomotive industry, Insurance Industry, Food and Beverage Industry, Dental Industry etc.

A) Usages of Dashboard Tools in Automotive Industry  Customer Relationship Management (CRM): Marketing Dashboard Tools integrate with automotive’s lead and appointment data, they work with just about every provider (Vinsolutions, Eleads, DealerPeak, Pro Max, CRM Suite, Higher Gear). Nothing is done by Manual.  Inventory Checking: Historical and current inventory is sync’d, Marketing Dashboard Tools also update multiple times per day automatically.  Digital Connecters: If the Automotive Industry grant them permissions to establish a platform like Facebook, Twitter, YouTube, Google and others social media and they connect to their own Applications.  Google Analytics: Marketing Dashboard Tools add automotive industry’s website to Google Analytics and SEO of Google and we take care of the rest  Custom Audiences: Automotive Industry’s data and Marketing Dashboard Tools learning predictions pushed directly into your Facebook Ad Account.  Business intelligence solution: Marketing Dashboard Tools provides the luxury of having all of your key dealership metrics consolidated into one dashboard.

B) Implications  By gaining insight regarding customers, companies can do effective management of marketing budget.  This analytics has the potential to inform automakers about the impact of incentives on a specific model, in a specific geography for a specific customer type.  Dashboards and planning tools will enable original equipment manufacturer (OEMs) to better plan make data driven decisions on allocation of finite marketing spend. C) Opportunities  From this tool they can get advertising & incentives properly. So, there is opportunity to drive both increasing sales performance & profitability.  Connecting with all types of social media and Google SEO, it creates opportunity for marketers to reach more customer with new car design.  By measuring vehicle sales rate and growth rate, companies can measure the effectiveness of websites or different campaign over online that help companies to invest for promotion wisely.  Counting number of customer and visitors who visit in online may create opportunity to induce them with different car models based on their interest they show by clicking online car advertisement.  By expanding the organization’s knowledge of KPIs, it enables the companies to take smart business decision about the direction of all current market situation, which creates opportunity to come up with new ideas.

D) Challenges  As it is a statistical tool, there requires enough skilled employees to manage or run the program. But it is also a challenge for automobile company to have skilled employees always.  The data collected & analyzed using dashboard tools maybe sometimes incompatible. So, it may make the decision difficult.  As people are more concern about security and aren’t willing to give their own information. For that reason they may feel insecure to visit website. So, it maybe challenge for automatic industries in future to have more information regarding customers.

Insurance Industry With as many real-time issues as insurance clients face on any given day, they can’t afford to be making uninformed business decisions. For that the insurance industry may use marketing dashboard tools to conduct or communicate with their clients. Businesses in the Insurance Sector collect data in volumes. From policies and premiums, to claims and pay outs, data is recorded all the time. But with so much information being collected, it can be difficult to bring it all together and realize the value that’s lying within.

A) Usages of Marketing Dashboard Tools  Marketing dashboard tools connect to multiple sources of data, from various departments, and display them side-by-side in a centralized dashboard.  All data shown in real-time using this tools. Putting the data at the user’s fingertips it allows them to visualize it in charts and graphs.  For using structured data and knowing customer insight insurance companies can lunch effective marketing campaign what their customer want.

Figure: The usage of analytics in insurance industry

B) Implementation  Improving customer-centricity Customer centricity has become the very fundamental goal of every industry and same is the case with the health insurance industry as well. Clients or patients want a trusted consultant who can help them avail the insurance service that they actually need. Health insurance analytics can help brokers fulfill that role. Insurance companies can now allow agents to take the help of health insurance analytics to gain actionable insights based on the data of the customer. With the help of health insurance analytics, instead of blindly coldcalling, insurance companies can call when they know their client is actually missing something they need. This will make the client feel like the insurance provider is actually looking out for them. 

Preventing frauds

Health insurance analytics tools have the ability to identify people who are most likely to commit insurance frauds. The data obtained would allow companies to develop plans to overcome instances of frauds and monitor insurance-related data in real-time. Leveraging insurance analytics would also prevent companies from losing money in the name of false insurance promises. 

Reduction in costs

Leveraging insurance analytics tools would help customers and clients to drive their overheads, speed up their claim processes, and optimize operational efficiency. Moreover, such tools also help companies to implement the appropriate network discounts, physician incentives, accurate pricing models, and optimal fee schedules. The data obtained through insurance analytics can help target high-cost demographic areas efficiently. 

Quality care and treatment

Health insurance analytics also helps improve the quality of consumers or patient’s care, while simultaneously regulating and controlling costs to provide better care for less money. Predictive algorithms can be brought into use to enable savings, direct decision-making, and bring about efficiencies.

C) Opportunities:  The challenge for most insurance companies, given their fixed marketing budgets, is to decide where to allocate resources to obtain the best marketing return on investment. Analytical tool helps address this problem.  For a new customer, customer lifetime value is normally determined using only demographic details. And this demographic details can be obtained by tracking information from customers using dashboard analytics tools, which help marketers the opportunity to provide lifetime value & create loyal customers that increase profitability.

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This analytics model can help insurance firms classify their existing clients into Platinum, Gold, and Silver categories. So, the opportunity is that through this classification it will not only motivate customers to purchase but also encourage them others to purchase policy from that insurance company. It provides a central location for users to assess, interact & analyze up-to-date information so they can make smarter data driven decision.

D) Challenges  Putting in place a broader data strategy to make more business-ready information available to analyst and business team.  Modern digital age competitors are challenging the business model of incumbents making them embrace digital transformation or become extinct.