Customer Relationship Management Improvement using IoT Data

Christian Ploder

, Reinhard Bernsteiner

, Thomas Dilger

and Sarah Huber

Management, Communication and IT, Management Center Innsbruck, Universit

atsstrasse 15, 6020 Innsbruck, Austria

Keywords:

Internet of Things, Customer Relationship Managment, Customer Centered Approach.

Abstract:

The Internet of Things (IoT) increasingly gains importance and costumers ale willing to pay for. Studies

show that by 2020, more than 30 billion devices will be connected and the IoT platform market will grow to

$ 7.6 billion in 2024. The purpose of this paper is to determine how IoT data could have a positive impact

on customer relationship management (CRM). An empirical study has been conducted based on qualitative

research methods with twelve experts in 2020 specialized in innovation marketing or CRM who have already

participated in IoT projects in the retail industry. The results demonstrate that companies will be able to

satisfy the customer’s needs in a more precise way and that it is possible to predict the customer’s behavior by

analyzing generated data. Furthermore for most companies it is sufﬁcient to implement a standardized CRM

system because of their lack of knowledge in software development and interfacing opportunities. In this way,

collected IoT data of the individual can be aggregated with already generated data from all other channels.

Through this alignment, a holistic customer understanding about the purchased products, services, and wishes

will be acquired and marketing activities can be targeted accordingly.

1 INTRODUCTION

Due to technological developments and the increas-

ing inter-connectedness of the world population, the

Internet of Things (IoT) has become reality (Abdul-

Qawy et al., 2015). Devices such as smartphones,

household appliances, machines, containers, vehi-

cles, and people or even entire cities are increasingly

connected to the internet. Equipped with sensors,

they can communicate with each other (Hanselmann,

2015). They report their status, receive instructions,

or take action on their own based on the information

they receive. According to estimates by the Ameri-

can market research institute Gartner Inc., the number

of networked things in 2020 will be about 26 billion

worldwide. Due to the forecasted enormous growth,

the IoT is attracting signiﬁcant attention among ex-

perts (Lo and Campos, 2018).

Moreover, the IoT can fundamentally change the

way of interaction between humans and their environ-

ment. The ability to electronically monitor and con-

trol objects in the physical world enables automated,

data-driven decision-making to optimize systems and

processes’ performance, and improve the quality of

https://orcid.org/0000-0002-7064-8465

https://orcid.org/0000-0002-8142-3544

https://orcid.org/0000-0001-7534-6514

life. Furthermore, the IoT can signiﬁcantly change in-

formation technology’s reach by interconnecting the

real physical world with the digital world (Lo and

Campos, 2018). In order to keep pace with this de-

velopment, companies have to exploit new technolo-

gies and need agile structures that adapt to changes.

Next to developing their technological infrastructure

in line with this trend, companies have to investigate

customer requirements. This valuable knowledge can

be implemented for instance to improve the area of

project management in order to deliver even better re-

sults to customers (Ploder et al., 2020). Besides, mar-

keting beneﬁts from the technological development.

Being always in touch with the customer after signing

a contract or selling a networked device enables new,

service-supported business models (De Cremer et al.,

2017). Every customer expects something different in

terms of customer experience, interaction, and busi-

ness relationships (Nguyen and Simkin, 2017).

Numerous research studies have been conducted

on the technical aspects of IoT (Atlam et al., 2018). It

could get difﬁcult to gain a comprehensive knowledge

of what exactly IoT means and its possible implica-

tions for Content Relationship Management (CRM).

It seems that the potentials of acquired IoT data are

insufﬁciently promoted. Besides, thinking in terms

of customer problems, system alliances will take on

a whole new meaning. Although there is a quite

Ploder, C., Bernsteiner, R., Dilger, T. and Huber, S.

Customer Relationship Management Improvement using IoT Data.

DOI: 10.5220/0010378101150122

In Proceedings of the 6th International Conference on Internet of Things, Big Data and Security (IoTBDS 2021), pages 115-122

ISBN: 978-989-758-504-3

115

extensive literature focusing on technological use of

IoT regarding business, marketing opportunities and

customer relations have not yet been sufﬁciently ex-

plored. Technological innovations offer numerous

new opportunities for the society which marketers in

the B2C sector should focus on (Jara et al., 2012).

Even tough traditional marketing principles remain

present, technological innovations allow businesses

and consumers to move closer together. Nguyen and

Simkin (2017) found a few research gaps in IoT Mar-

keting, such as integrating IoT channels and commu-

nication strategies or consumer engagements. As this

development will continue, companies need to adapt

to the latest trends and respond to customer requests

as quickly as possible (Oglesby, 2018). Therefore,

this paper shows how IoT technologies can improve

CRM. It is intended to serve as ‘food for thought’ re-

garding future IoT scenarios in CRM and how best

practices could apply to different areas. Therefore,

the research question applies to customer goods and

retail industry and is the following: How can IoT data

improve Customer Relationship Management?

After the introduction in section 1, section 2 out-

lines the theoretical concepts followed by explaining

the empirical study design in section 3. The results

are presented and discussed in section 4 followed by

a conclusion in section 5. Finally, Section 6 states

the limitations of the proposed approach and hints at

future research directions.

2 THEORETICAL BACKGROUND

To gain a piece of comprehensive knowledge about

the terms used for this paper, this section shows def-

initions and explanations of the most important ones

for the given research: digital marketing, IoT, CRM

in digital marketing. To combine the terms in answer-

ing the research question, the last subsection is about

the use of IoT in CRM.

2.1 Digital Marketing

Kotler, Kartajaya, and Setiawan (2010) became the

ﬁrst authors discussing the evolution of Marketing

and starting with Marketing 1.0, which concentrates

on a product, followed by Marketing 2.0, focusing

on the customer, up to a humanistic Marketing 3.0,

which turns a customer into a human being. As a con-

sequence of these inﬂuences, successful businesses

have to develop products, services, and corporate cul-

tures that reﬂect human values. Currently, compa-

nies are transitioning into Marketing 4.0, which will

deepen and broaden customer-centric marketing. It

does not imply that traditional advertising media such

as print, posters, or television advertising will disap-

pear immediately from one day to another. A com-

bination of ofﬂine but more online marketing will re-

tain its functions, such as publicizing a brand in the

ﬁrst place. Nonetheless, the signiﬁcant stimuli for

sales promotion are already being generated by on-

line channels and will increasingly continue to do so

in the future. That signiﬁes a shift of power towards

consumers (Kotler et al., 2017).

Simultaneous to this development, Marketing

conditions have continuously changed since the broad

introduction of the Internet in the early 1990s. The ap-

plications and opportunities associated with this ﬁrst

period of the Internet are also designated as Web 1.0.

In 2004, O’Reilly (2009) started to use Web 2.0 to

describe people taking part in the Internet. According

to Kreutzer (2016), the main characteristic of Web 2.0

is about active user participation. Hence, the poten-

tial of collective intelligence can be exploited to the

greatest extent through the possibility of changing the

contents by oneself and presenting one’s creations.

So-called user-generated content, i.e., content created

and published by the internet users themselves, is a

core element of Web 2.0. Several examples include

forums and internet blogs for various topics.

2.2 Internet of Things

Concerning the hype about the concept of the IoT in

recent years, it is not surprising to see many attempts

to deﬁne the term. No ofﬁcial or unambiguous def-

inition has been found in the literature (Dorsemaine

et al., 2015). According to Atzori et al. (2010), dif-

ferent deﬁnitions exist because companies, research

institutions, or stakeholders, depending on their inter-

ests or backgrounds, either see IoT from an internet-

oriented or thing-oriented perspective, and accord-

ingly ﬁnd deﬁnitions in varying ways. Kevin Ashton,

director of Auto-ID Center at MIT (Massachusetts

Institute of Technology), and his collaborators are

considered the inventors of the term IoT but used a

rather long and sophisticated deﬁnition (Ashton et al.,

2000). Since then, numerous terminologies have been

published due to the technological development in

IoT (Abdul-Qawy et al., 2015). Stephan Haller of

SAP Research deﬁnes the IoT in a concise and pre-

cise way: “A world where physical objects are seam-

lessly integrated into the information network, and

where the physical objects can become active partic-

ipants in business processes. Services are available

to interact with these ‘smart objects‘ over the Inter-

net, query their state, and any information associated

with them, taking into account security and privacy is-

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116

sues.” (Haller et al., 2009, p. 15). The authors (Atlam

et al., 2018, p. 928) add that “IoT can be considered

both a dynamic and global networked infrastructure

that manages self-conﬁguring objects in a highly in-

telligent way”. Whenever IoT is mentioned in this

paper, the deﬁnition always refers to Stephan Haller’s

description as it includes all essential elements and

is comprehensible. Despite the multitude of different

deﬁnitions of the IoT, all have one aspect in common:

integrating the physical world into the virtual world.

Moreover, most authors agree that the IoT is designed

to provide an IT infrastructure that facilitates data ex-

change between things in a secure and reliable man-

ner (Weber, 2010). Nicholas Negroponte explains the

use of IoT, combined with the right technology such

as RFID as: ”It’s about embedding intelligence, so

things become smarter and do more than they were

proposed to do” (Vidalis and Angelopoulou, 2014, p.

15). Hence, the IoT is not only the interconnection of

an object with the internet. (L

opez et al., 2011, p. 285)

restrict the deﬁnition as follows: ”A ‘smart object’

is any object or product that is –by way of embed-

ded technologies –aware of its environment and state,

and it may have the ability to make its own decisions

about itself and its uses, communicate state informa-

tion, and achieve actuation under its control.” To rep-

resent a smart object in the context of the IoT, it is not

sufﬁcient that it is only readable, recognizable, local-

izable, and addressable (Ibarra-Esquer et al., 2017). It

is not enough to store data. Data have to be processed

to react dynamically to changes (Minteer, 2017). Be-

sides, a smart object should be able to respond au-

tonomously (van Deursen et al., 2019). Consequently,

it has to be equipped with software to act indepen-

dently online without human intervention. That, in

turn, requires that the smart device access the Inter-

net (Fortino and Trunﬁo, 2014). If these prerequisites

are fulﬁlled, it can be seen as a smart object in the IoT

and could be used to support CRM.

2.3 CRM in Digital Marketing

A consistent orientation of all entrepreneurial activi-

ties towards the market is crucial to distribute the of-

fered products and services (Herhausen, 2011). Bruhn

(2016) describes Marketing as analyzing, planning,

implementing, and controlling internal and external

company activities that aim to achieve sales by align-

ing company performance with customer beneﬁt in

the sense of consistent customer orientation. Accord-

ing to Bloching et al. (2012), traditional advertising

efﬁciency has been declining for years across all seg-

ments. The main factors are the multiplication of cus-

tomer segments, products and brands, media and dis-

tribution channels, and international competition’s in-

tensiﬁcation in our globalized world (Bloching et al.,

2012). Whereas digital marketing causes compara-

tively low costs and generates a better-targeted au-

dience (Dodson, 2016). Due to IoT’s technical

abilities, it will be even easier to recognize neces-

sary factors of consumer demand in a more detailed

way (Nguyen and Simkin, 2017). It empowers com-

panies to understand customers and personalize tech-

nical products and services (Hoffman and Novak,

2018). Conversely, increased customer satisfaction

leads to stronger customer loyalty, which has a pos-

itive inﬂuence on the company (Kumar and Reinartz,

2018).

Customer Centricity is a sales and marketing con-

cept focusing on the customer rather than on the

product (Shah et al., 2006). The value chain is de-

signed in the following way: The expectations, needs,

and wishes of the individual are the starting points

for marketing activities (Gummesson, 2008). Hu-

man needs are a lack of something that they need

because of nature. Purchase intentions are decisions

of particular satisfaction seekers who also want to

acquire something under given conditions. A pur-

chase is then the actual acquisition of the speciﬁc

satisfying person (Lo and Campos, 2018). As a

new customer, the person will provide new initial

data. As a returning customer, the person allows

an even more personal relationship between the cus-

tomers and the company (Waisberg and Kaushik,

2009). At the point of post-sale, long-term efforts be-

come visible of how a company deals with customers

who have already bought products (Reynolds, 2002).

Cost beneﬁts of keeping a customer is a reason why

customer-centricity is not only about ﬁrst-time pur-

chases, but more about long-term customer relation-

ships that may last a lifetime (Shah et al., 2006).

2.4 Use of IoT in CRM

Location-based technologies (Ko

uhne and Sieck,

2014) enable the use of the customer’s current loca-

tion for marketing purposes. Location-Based- Ad-

vertising (LBA) “is a new form of marketing com-

munication that uses location-tracking technology in

mobile networks to target consumers with location-

speciﬁc advertising on their mobile devices” (Telli

Yamamoto, 2010, p. 125). In contrast to location-

based marketing, proximity marketing makes it pos-

sible to locate customers precisely to inches and de-

liver content even more effectively than location-

based marketing (van Deursen et al., 2019). For

example, this allows a retailer to reach customers

who are just passing their store. Geofence or GPS,

Customer Relationship Management Improvement using IoT Data

117

Bluetooth Low Energy beacons, and WLAN are the

most common technologies used in proximity market-

ing (Rieber, 2017). Some department store brands are

using Apple’s iBeacon technology and a mobile mar-

keting platform to provide customized promotions

when downloading the brand’s app. The customer

can be informed about products or special promotions

in the retail store via beacons during shopping. By

reading the QR code or the NFC tag on the prod-

uct, he can receive detailed background information

about the speciﬁc product, such as what the product

is made of, size, ingredients, warranty, instructions

for use and cleaning (Kruse Brand

ao and Wolfram,

2018). Another possibility is NFC tags, which are

small transponders that provide information on the

mobile phone. It is sufﬁcient to place the telephone

within a range of a few inches of the transponder. In

contrast to a QR code, the NFC tag can also be hid-

den and therefore built into objects (Kruse Brand

and Wolfram, 2018).

Every experience that a customer gains with a

smart product, a supplier’s staff, a store, or a call

center is a moment that can inﬂuence the brand di-

rectly (Nguyen and Simkin, 2017). For instance,

Google provides the smart thermostat Nest, which

takes over the intelligent temperature control (Gre-

gory, 2015). It learns when the owners are at home

and in which room they are. The temperature in each

room is then adjusted accordingly, so the customer

always feels comfortable. Besides, it saves energy

costs and in the same time, the environment is pro-

tected trough a lower energy consumption. Brands

like Google use Customer Experience Management

(CXM) as a critical differentiation to attract cus-

tomers and engage and retain them. Thus, CXM no

longer implies merely selling a product but creating

added value and a close exchange between a brand

and its customers - a shift from pure product sales to

provided services (Gregory, 2015).

3 EMPIRICAL STUDY DESIGN

To answer the given research question in section 1, the

qualitative approach of Mayring (2010) was consid-

ered the most appropriate methodology to get insights

into this research area, since the combination of IoT

and marketing as well as CRM activities are not suf-

ﬁciently explored. Due to this reason, an exploratory

study is the best way to extract not only new insights

but also recommendations.

According to Flick (2007), the focus of an expert

interview is less on the interviewee as a person than

on his or her capacity as an expert for a particular ﬁeld

of action. Considering the expert’s knowledge, their

individual deﬁnition of IoT and practical experiences,

expert interviews can give more in-depth insights into

IoT Marketing and Services’ current state.

For the purpose of this study, experts were se-

lected based on the following criteria: (1) limited to

consumer goods and retail industries, (2) employed at

an international company, (3) age group 25 to 50, and

(4) academic background and involved in data-driven

marketing projects. The recruitment of the experts

was done via telephone based on multiple searches.

In the end, 12 interviews have been conducted, mainly

in Europe. The experts’ professional ﬁeld and gained

experience in either a customer goods segment or re-

tail industry are given for all of them.

To stimulate the expert’s creativity initially, they

were asked to read three business scenarios before-

hand provided by the researchers. Furthermore, the

scenarios gave the interviewees the possibility to re-

fer to those examples while answering the following

interview questions. Those were created based on the

identiﬁed gaps in the literature. To gain as much infor-

mation as possible from the interviews and to keep the

ﬂow of the expert’s speech uninterrupted, the ques-

tions were not asked in a strict order.

The experts were asked questions around the fol-

lowing topics: (1) their deﬁnition of IoT, (2) Current

known and future application ﬁelds of IoT technology

for CRM activities as well as beneﬁts and challenges

of it, (3) Characteristics of a good CXM and how

to engagement consumers, (4) IoT support possibili-

ties in marketing and CRM. Thereby, participants was

given enough freedom to elaborate on their knowl-

edge and experiences. In the end, the experts were

also ask to reﬂect on the interview and state any addi-

tional comments.

After recording all the interviews, they have been

transcribed using the software Trint

in a denatural-

ized manner. This simpliﬁed process focused on the

content. The researchers aimed to standardize the

data and correct interview noises or minor grammat-

ical errors (Oliver et al., 2005). Applying the induc-

tive method, categories were not created before the

material was viewed, but were derived directly from

the material, without referring to theoretical concepts

used in advance (Mayring, 2010). For evaluating all

information obtained, the professional analyzing tool

MAXQDA2

was chosen. Dominating topics were

identiﬁed that seemed relevant for the analysis and

were extracted by ﬁltering the material. For this pur-

pose, coding of the text was necessary, which took

place on creating a keyword index.

https://trint.com

https://www.maxqda.de

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118

Furthermore, the authors suggest verifying the codes

after working through 10-50% of the material. The

authors reviewed the categories for appropriate pro-

portions and possible designations after 30%. Subse-

quently, individual types were summarized. Accord-

ing to Krippendorff’s Alpha, to measure the reliability

of the intercoding, a test was carried out and showed

a result of 70,31. Mayring (2010) and Krippendorff

(2004) require values of at least 67. Since the inter-

coder only got a brief introduction to the topic and the

coding system, this can be considered sufﬁcient reli-

ability testing as the coefﬁcient is above the recom-

mended 0,67 (0,73). After explaining data collection,

the next section will show the results of the study.

4 RESULTS

During the data analysis of the twelve expert inter-

views more than 450 codes have been detected with

the inductive research strategy based on qualitative re-

search methods Mayring (2010). Based on the codes,

the experts statements were classiﬁed into 17 differ-

ent categories and afterwards grouped under the three

main topics of (1) Internet of Things, (2) IoT Mar-

keting/ CRM and (3) Future Implementations. Ta-

ble 1 shows the frequencies of the aforementioned

categories.

Table 1: Coding Process Results.

Main Topics / Categories Frequency

Internet Of Things

Analyzing Data 29

IoT Data vs. Big Data 29

IoT Deﬁnition 21

IoT Marketing/CRM

Customer Experience Management 47

Data Collection & Tracking 37

Measurability & KPIs 37

Targeting 37

Purpose Marketing Activities 32

Engagement & Review 27

Changing Customer Journey 25

Customer Needs & Behavior 23

Customer-Centric Service 17

Future Implementations

Future of Retail 48

Future of Wearables 29

General Future Perspective 20

Recommended Actions 20

Future of Dash Buttons 19

In the following subsections serve for a detailed ex-

planation of frequent mentions in the interviews. The

categories of Analyzing Data, Customer Experience

Management and Future of retail were chosen based

on relevance to the research topic and frequency of

occurrence. Therefore every quote is related to a par-

ticular Interviewee (I) with a text mark for traceability

reasons (number).

4.1 Analyzing Data

According to I2 (31), companies evaluate already

generated data insufﬁciently, although enough infor-

mation is available. Time pressure is an often cited

reason. In some cases, there is also a lack of qual-

iﬁcations to evaluate data correctly mentioned (I2,

33). Another interviewee sees a challenge in analyz-

ing data ”if you combine the data from two different

sources. That’s not exactly the value that you get. You

have to make sense of what is coming out from both,

and then you can do something new” (I9, 11). ”I have

to say maybe 95 percent or 99 percent of the advertis-

ing I see is not even relevant for me. I would rather

have less advertising but the ones which I maybe care

about” (I9, 7). The reason is ”if you have terabytes

and terabytes of data it’s practically useless because

you cannot build any correlations” (I9, 21). I9 (31)

mentions that data would not tell the employees how

they want to be processed and analyzed, of course.

According to I9 (29), ”the worst thing that a company

or individual can do is ﬁrst to collect the data and then

start thinking what do I need to do with all of this be-

fore collecting the data. Before doing anything, you

need to be clear on what your end product is”. There-

fore, it is necessary to think about the right questions

before businesses start to collect data for later use in

marketing activities. For instance, which products are

purchased at what time and in what quantity (I5, 16).

Moreover, the analysis of consumer behavior

should propose order suggestions based on the pref-

erences of customers ”because I decided to organize

a barbecue quickly, I drove past the store and bought

Jever. Then Alexa could suggest Jever to me the next

time I order a beer. And that’s why branding is so

important because I don’t say to Alexa order a six-

pack of Jever ; I’d probably say order a six-pack of

beer ”(I4, 20).

4.2 Customer Experience Management

”Customer Experience Management is successful if

the customer is enthusiastic” (I2, 21). An essential

point for Interviewee 10 (19) is an appropriate cus-

tomer experience for the product. ”I don’t want to be

forced to have an excessive customer experience for a

trivial product” (I10, 19). In addition, ”it is simply im-

Customer Relationship Management Improvement using IoT Data

119

portant that the communication is not exaggerated. If

you are constantly approached with consumer goods,

I think there will be a ﬂattening out or a sealing off

of the consumer. That’s why it will be imperative that

the customer experience also considers providing the

right amount at the right time to address the customer.

Maybe you can do that again with wearables” (I10,

19). By ”talking to my Alexa the company hopefully

knows which tonality I prefer, and subsequently, the

company could send an email that matches my tonal-

ity and not the initial slogan” (I4, 32). For I3 (29), the

correct use of already generated customer data is not

only an advantage, but also desired: ”Now I down-

load the Smart Home App for my dishwasher with the

same e-mail address. In the best case, this would al-

ready provide a link based on your order data, which

you also submitted. Do you agree that we use the

data for the order?” (I3, 29). This enables companies

to address customers precisely and make assessments

based on where they live, and the social-economic

background could be taken into account (I3, 29). I3

(21) further explain using the example of a malfunc-

tioning, smart dishwasher, service staff could already

see in their CRM system which model the customer

has, how often it has been used and which program

is used most often. The networked technology allows

sensors to detect that a dirty pump. Now the customer

can decide whether he wants to solve the problem

himself or whether a technician should take a look.

Even more innovative solution companies could con-

sider ﬁnding the failure before the customer recog-

nizes that something is not working and subsequently

inform the customer to offer various options (I3, 21;

I7, 29). However, I1 (35) says that companies should

demonstrate transparency on the one hand, but on the

other hand, they should not scare the customer by let-

ting them know that they have detailed data stored (I3,

27). Therefore, I3 (27) recommends the continuous

checking of data and touch points for improvements,

which could lead to new product developments and

eliminate user research.

4.3 Future of Retail

”I’m not sure if we will have an Amazon Go similar

story in Germany now due to the regulations. But I

think it will move in this direction” (I12, 3). The food

sector is predesignated for this kind of concept since

customers need not much consultation: ”In general, I

think that consulting will become less due to the pos-

sibility of getting information through the web, new

technologies, smartphones, wearables, etc. or during

the buying process” (I12, 3). Conversely, it could be-

come more difﬁcult for expensive products in need of

explanation (I12, 3). The time factor (17, 5; I1, 3;

I4, 5) and the convenience for customers (I7, 3; I2,

3) were mentioned as advantages of IoT retail, but at

the same time, companies can also save costs through

less personnel (I8, 3). I8 (3) believes that this con-

cept might be interesting for several companies in the

game, i.e., not only for marketplace providers but also

for payment providers. Beneﬁts from all the customer

information would attract shop operators and compa-

nies like PayPal or Mastercard. I10 (3) thinks that

Apple Pay could establish itself as a future payment

option in stores since contactless payment with mo-

bile phones is simple and secure. ”I believe that the

barrier to such services, mostly based on sensor tech-

nology and networking with RFID technology, will

decrease and that acceptance will increase and then

spread very quickly. I would almost say that this will

be disruptive” (I20, 3). The expert adds that intro-

ducing this technology in countries such as Asia or

the US will be relatively quickly established. Still, in

Europe, it might take longer in terms of data security.

Also, technical equipment and operation overhead are

currently still expensive.

However, most of the experts agreed that re-

tail’s future is moving towards concepts like Amazon

Go. ”I think convenience will prevail in everything,

whether privacy or anything else” (I6, 3). Further-

more, ”the pain at the checkout is high enough” (I6,

3). I2 (5) could imagine a similar concept for petrol

stations. Nowadays, people are very busy; if they are

on the highway, they want to be at their destination

quickly. The interviewees see an advantage in an au-

tomatic recording system that can identify the license

plate number and debit the credit card amount. The

fashion industry could also beneﬁt from the use of IoT

technologies (I6, 5; I7, 9). I6 (5) states an example:

”I can take a look into virtual shopping carts, so to

speak, at what people trying on, what they don’t like”

(I6, 5). Accordingly, businesses can examine whether

they do no longer order individual clothes cuts.

5 DISCUSSION

Based on the literature research and the qualitative

empirical study, the authors investigated how IoT data

can be used for CRM and which impacts occur in the

relationship between companies and customers.

All of the interviewed experts agreed on the retail

industry’s future moving towards self-service, such as

Amazon Go. Furthermore, it is crucial to implement

a standardized CRM system, aggregate collected IoT

data of the individual, and align them with already

generated data from all other channels. A holistic

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120

customer understanding about the purchased prod-

ucts, services, and wishes will be acquired through

the alignment of all data.

Once the customer purchases an IoT device, com-

panies can retrieve data and contact the customer. Lo

and Campos (2018) laid out that thereby, companies

will be able to more easily satisfy the customer’s

needs. Besides, it is even possible to predict the cus-

tomer’s behavior based on the analysis of collected

data. In that sense, it is essential to focus on operating

in a customer-centric way throughout all activities as

already found by Shah et al. (2006). Delivering an in-

dividual customer experience, the customer-centricity

approach supports the creation of new business mod-

els within the context of IoT. To that extend, the use

of IoT in CRM allows for more tailored services and,

thus, more revenue to generate. Businesses need to

align omni-channel and cross-channel for their com-

munication to reach their respective customers Lo

and Campos (2018). This is because the customer

decides about the channel of interaction. In other

words, companies should not only maintain contact

with their customers via all touch points but also pay

close attention not to disadvantage customers based

on their communication preferences. The retail indus-

try especially can create a more comprehensive and

improved ecosystem and enable bi-directional real-

time interaction with consumers inside and outside

the stores Nguyen and Simkin (2017). Through the

fact that most customers are permanently online via

their smartphones, retailers should use this device as

a touch point for all interactions to exploit the poten-

tial of IoT integration. Therefore, as found in the in-

terviews location-based beacon technology is an op-

tion for retailers to interact with their customers when

entering the store directly. Based on the beacon tech-

nology, the customer can be informed about products

or special promotions in real-time at the retail store.

From a customer’s perspective, that helps to encour-

age a purchasing decision. Altogether, this shows

how IoT data can be applied to improve CRM.

6 LIMITATIONS AND FUTURE

RESEARCH

Since twelve experts were interviewed for this empir-

ical study, the consent may not reﬂect the entire popu-

lation’s opinion or understanding of IoT applications

in CRM. Therefore, the results are not generally valid,

as most of the experts come from Europe. Due to the

subjective selection of experts, a distortion of the re-

sults may occur. Furthermore, it cannot be excluded

that the experts have a positive perspective on the sub-

ject due to their attitude and proximity to the survey

topic. Besides, it wasn’t easy to classify the answers

of the interviewees into the respective categories. As

there were frequent overlaps of the content, it wasn’t

easy to draw clear boundaries. This paper focuses on

future marketing and CRM processes and tries to pro-

vide the ﬁrst impulse for IoT in marketing. Never-

theless, there is a need for a much more deepened

understanding of the effects of IoT. Particular atten-

tion should be paid to communication and marketing

strategies designed for IoT purposes aiming to reach

customers according to their needs. Further quanti-

tative research should be conducted to identify how

consumers perceive tailored promotions and services

instead of traditional marketing measures.

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