Business Information Systems Dersi 5. Ünite Özet

The Definition of Marketing Information Systems (MKIS)

According to Kotler MKIS can be defined as “A structure consisting of people, equipment, and procedures to gather, sort, analyze, evaluate, and distribute needed, timely, and accurate information to marketing decision makers.”

Managers or employees at every level of an organization (ranging from operational specialist to manager and CEO) use information to improve not only their personal performances but also the marketing performance of the firm. MKIS is concerned with information flowing from the environment to marketing managers.

The widening role of MKIS results from development in electronic technologies that allow faster and broader flow of information not only within the company but also within the society. In the era of information, it is rather easy to gather information for decision making purposes.

However, because of the high quantity of information, the borders between true and falso data have been disappeared the importance of information literacy, which means a set of skills that enables managers to seek, evaluate and use information in an effective way; have been indicated.

MKIS provides a continuous process that has a future orientation, marketing research (MR) is about solving a problem and specific situation. Market research is the systematic design, collection, analysis and reporting of data and findings relevant to a specific marketing situation facing the company.

Types of Information in MKIS

Three distinct types of information are generally supplied to marketing managers for decision making purposes;

• Recurrent information is information that is provided on a periodic basis from periodic reports.
• Monitoring information is derived from the regular scanning of certain sources.
• Requested information is developed in response to a specific request by a marketing manager.

Sources for Marketing Information System

A company may gather information from both inside and the external environment of company. Internal information sources and records such as accounting records or customer records provide information about customers, sales, costs, inventories, buying habits and timing, the reactions of distributors, suppliers, intermediaries, etc. Internal information may be obtained from company’s own employees - executives, managers, engineers, scientists, buyers and sales staff.

Information from internal sources can be accessed faster and cheaper than information from other sources, but internal information gathering has some shortcomings, too. On the other hand, a company may also benefit from its suppliers, intermediaries and customers for obtaining valuable information.

The commercial interaction between the firm and its customers may offer a great deal of information including:

• Total sales or sales volüme over time,
• Regional sales,
• Sales voluma by market segment,
• Sales by trade category,
• Sales volume by type of channel of distribution,
• Pricing information,
• Communication mix information,
• Sales representatives’ records and reports,
• Inquiries or complaints received.

Another way of gathering information is marketing research. Marketing research is the systematic gathering, recording, and analyzing of data about problems relating to the marketing of goods and services. Systematically designed, collected, analyzed and reported data set and findings relevant to a specific marketing situation challenging a company might answer questions about new product development, promotions, pricing, packaging, distribution or competitive action. Research aimed at solving a specific, pragmatic problem is called as applied marketing research. On the other hand, companies may want to expand the borders of knowledge without aiming to solve a specific problem. In this case they do basic market research to validate a theory, test hypotheses, learn more about a concept or phenomenon, such as nanotechnology, Internet of the Things etc. Effective marketing research involves five steps;

1. Defining the problem,
2. Developing a research plan,
3. Collecting problem specific data,
4. Interpreting the data and solving the problem,
5. Decision making.

As a common practice, companies use external data for forecasting market trends, benchmarking, validation of internal data and demographic analysis of potential markets. External data may be collected from different sources such as media channels, internet, and governmental institutions. The other external data sources are standardized sources of marketing data such as consumer purchase panels, store audits, multimedia services etc.

With the rise of social media, cloud computing, Internet of Things, mobile devices, RFID, GPS and, undeniably, computing power, these information flood is referred as big data. Consequently, this new term revolutionary transformed both MKIS and the ways companies operate. Big data is defined as such: massive data files that can be obtained from both structured and unstructured databases.

One should think of big data not only in terms of analytics, but more in terms of:

• Developing high-level skills that allow the use of new generation IT tools,
• The architectures to collect data from various sources,
• Storage, organization, extraction, interpretation of massive data to generate valuable insights,
• Sharing them with key firm stakeholders for competitive advantage co-creation and realization.

By the way, there are some shortcomings of using external data for decision making purposes such as;

• The necessary data may not be available, or it may need some transformations.
• The integration with existing company data sources or information systems may be problematic.
• Importing data can be time-consuming.
• It may be hard to ensure data compatibility.
• It may require manual work-flow and data processing.
• It may be difficult to validate data formats.

Although such a vast amount of technical developments is giving difficult times to companies, they are, at the same time, offering opportunities to firms such as integration of their internal data with external information sources. For example, Open APIs are great tools for MKIS. An open API, also known as a public API, is an application programming interface that allows the owner of a network-accessible service to give universal access to consumers of that service, such as developers.

Marketing Information System, Big Data and Marketing

It is obvious that the raw data are not useful to marketing manager. For this reason, we need a process which includes converting data to information. The first step in transform data into a competitive advantage is understanding the difference between data (recorded facts, things, events and statistics), information (formatted, useful data extracted from data pool), knowledge (internalized information) and insight (a deep level of understanding about a particular situation). Data becomes information when it provides answer to questions of “what”, “where”, “how much”, “how often” and “when”.

One final and essential point at turning data to smart data is forming a Marketing Decisions Support System (MDSS) within company. Marketing Decisions Support Systems are the systems that allow decision makers to connect directly to the database consisting of computers and communication networks.

At this point, big data often consists of high volume data that marketing managers can use to obtain valuable information and make more well-directed marketing decisions. Big data includes mountains of data collected from social networks, retailer scanning or media scanning, consumer purchases, store tracking, logistics, production, cloud computing, Internet of Things, mobile devices, RFID, GPS and many more sources. Below a piece of information is presented to give an idea of the bigness of big data and usages of big data in marketing decisions. These tiny piece of information given below is going to focus only on;

• The data collected for customers,
• The data collected for products,
• The data collected in a time-frame, and
• The data collected for a geo-spatial location.

Tracking technologies had enabled firms to move from aggregate data analysis when data was limited to individual-level data analysis that allows for much more granular targeting. All these efforts were for acquiring more customers in order to obtain competitive advantages. In marketing, the ability to track new customers and to link transactions over time is key. Loyalty programs are the most common way for such tracking. Besides, credit card, IP address, and registered user log-ins are also commonly used. Companies also have much better measures that links customer shopping/transaction data with marketing insight such as demographic data from credit card usage, survey data that is linked via email address, store visit information that can be tracked in a variety of ways or from a Customer Relationship Management (CRM).

Product information in marketing is defined by a set of attributes which define the product. Hence firms have product information matrices that are both dynamic, large and much more descriptive allowing for greater variation of product varieties that are microtargeted toward consumers. This is translated as competitive advantage.

While the data sets mentioned above for “customers” and “products” may seem large, imagine a third-dimension; “time” which literally multiplies the size of this data. That is, while traditional analysis in marketing has looked at data aggregated to monthly or possibly weekly level, data in marketing today comes with a time stamp that allows for continuous measurement of customer behaviour, product assortments, stocks/ inventories, in-store displays so on so forth.

Geospatial data describe objects and things with relation to geographic space, often with location coordinates in 3 a spatial referencing system. Geospatial data are collected using ground surveying, photogrammetry and remote sensing, and more recently through laser scanning, mobile mapping, geo-located sensors, geo-tagged web contents, volunteer geographic information (VGI), global navigation satellite system (GNSS) tracking and so on. The ability to use the spatial location of the customer at any given point in time has opened up a whole new avenue for marketing managers where customer’s geospatial location could impact the effectiveness of marketing, change what offer to make, determine at what marketing depth to make an offer, to name just a few.

If the customer’s geo-spatial location is tied to the CRM database of a firm, managers can unlock tremendous value where a customer’s purchase history is then tied to what products they are physically near to allow for hypertargeting at the most granular level. However, while this hypertargeting is certainly appealing, and short-term revenue maximizing, companies will need to consider both the ethical and potential boomerang effects that many customers feel when products are hyper-localized.

Despite all the glitz, MKIS evolution brings some ethical considerations and a number of challenges to the agenda. The greatest challenge is consumers’ hesitation or concern to use technologies such as locationbased technologies, cookie tracking, beacon-based tools etc. Besides, companies can tend to abuse the respondents. Respondent abuse can take several forms. Perhaps the most common is lengthy interviews. It is not uncommon for companies to request additional “nice to know” questions, or even exploratory questions on an entirely separate project. This leads to long questionnaires or long interviews which leads the respondents to refuse in participating surveys. On the other hand, many research studies appear to be little more than vehicles for pitching the sponsor’s products. In fact, in some cases, the research surveys appear to have been designed just to produce the intended effect.