Tag Archives: customer analytics

Implementing Social Customer Relationship Management in Retail

One of the most important goals for retailers is to maintain long-term and profitable relationships with their customers. The construct Customer Relationship Management (CRM) started when retailers moved the orientation of their business from their companies to their customers. However, the advent of the internet, Web 2.0, and online social networks have disrupted the traditional way that retailers communicated with their customers.  Hence, Social Customer Relationship Management (SCRM) came to the fore because of the emergence of a “social customer”.

Social customers comprise the 2.8 billion* active social media users (Dr Dave Chaffey *, Smart Insights, 27 Apr, 2017). With these billions of social media users, retailers are no longer in control of customer relationships. Instead, customers and their highly influential virtual networks are now driving the conversation, which can trump a retailer’s marketing, sales and service efforts with their unprecedented immediacy and reach 1. However, social media needn’t to be a threat for retailers. Indeed, retailers that learn how to use social media technology to their advantage can gain valuable insights about the demographics and buying behaviour of their customers.

The use of technology for successful Social Customer Relationship Management

Social networks offer retailers practicing Social Customer Relationship Management masses of customers who group themselves around a brand 2. It is here, in these networks, that retailers can study the community’s behavior toward a brand or firm beyond purchase. The data originate from motivational drivers such as word-of-mouth activity, recommendations, customer-to-customer interactions, blogging, and the writing of reviews 3.

But retailers haven’t yet realized the opportunities of using their own data resources for Social Customer Relationship Management. Sandra Gittlen, mentioned  the following recently in CIO: “In an age where most companies have a social media presence on platforms such as Facebook, Twitter, LinkedIn, Snapchat and Instagram, it’s somewhat surprising that many still haven’t figured out how to turn the data gathered from company-owned properties and broader social media listening tools into automated and actionable intelligence”.

Trainor, Andzulis, Rapp and Agnihotri, (2014) 4 identified four functional blocks enabled by social media technology that are particularly relevant in a CRM context:

  1. Sharing – refers to technologies that support how users exchange, distribute, and receive digital content (e.g., coupons, texts, videos, images, “pins” on Pinterest, etc.). This is similar to the concept of information reciprocity – the activities and processes that encourage customers to interact and share information – which has been shown to positively influence a firm’s ability to manage relationships.
  2. Conversations – represents technologies that facilitate a firm’s interactive dialog with and between customers (e.g., blogs, status updates on Facebook and Twitter, discussion forums, etc.) and capture the information from these dialog.
  3. Relationships – represents the set of technologies that enables customers (and businesses) to build networks of associations with other users (e.g. Facebook, LinkedIn, Ning, Yammer, etc.) and allows organizations to utilize this network information.
  4. Groups – represents the set of technologies that support the development of online user communities centered on specific topics, brands, or products. Examples include SalesForce.com’s Ideaforce and Igloo’s Customer Community application software.

Integrating your Social Customer Relationship Management program with your marketing automation

SCRM deals with the strategies, processes and technologies that retailers can use to link the social web with their CRM strategy. According to Reinhold and Alt, (2012) 5, SCRM poses a challenge for large firms with numerous employees, market offerings and offices. Consequently, they need to discover the relevant conversation threads, synchronize information flows, initiate the appropriate actions and communicate at an individual level within millions of social web conversations.

However integrating SCRM with marketing automation is not impossible – you only need to start right. Malinda Wilkinson (DestinationCRM.com) advises that it’s important that your technology should always follow your process, not precede it. “Without this integration, it is difficult to create a consistent experience for your prospects and customers. And on top of that, too much time and too many resources will be drained trying to coordinate activities to ensure leads don’t fall through the cracks”, concludes Malinda.

Fitting your Social Customer Relationship Management program with your business philosophy

The success of an effective CRM system depends on the background marketing methods and business philosophy 2 of retailers. Therefore customer centricity should become the new strategic goal, where retailers build their brand and image together with their customers.

Linda Shea in AdAge.com proposes the following to become and remain a customer centric company:

  • Executives need direct interaction with customers. The key to executive buy-in, commitment and active support is first-hand knowledge and understanding of what is delivered to the customer, relative to their needs and desires.
  • All employees need to embody the intended customer experience. A narrative must be cascaded down to every single individual in the organization. Your employees must clearly understand their role in delivering the promise the narrative makes to the end customer.
  • Just say “no” to off-strategy ideas. Excitement abounds in most organizations with ideas and fresh thinking that may lead to new revenue streams. However, it is imperative to recognize that customer-centricity is not a destination but rather a multi-faceted, multi-year journey that will require laser-sharp focus, commitment and investment.

Concluding

Retailers that are not with their customers on the social networks will soon run out of customers. The Social Customer Relationship Management construct is customer centric by definition, giving retailers the opportunity, with the aid of marketing automation, to be part of the social media cloud.

Further reading:

  1. Finding Customers in the Vastness of the Internet
  2. Predictive Analytics helps Retailers to make sense of Big Data
  3. Demise of Loyal Retail Customers in the Digital Age

Notes:

1 Heller Baird, C. and Parasnis, G. 2011. From social media to social customer relationship management, Strategy & Leadership, 39(5):30-37.

2 Bagó, P. and Voros, P. 2011. Social customer relationship management, Global Journal of Enterprise Information System, 3(3):35-46.

3 Yoon, K. and Sims, J.D. 2014. Integrating Social Media and Traditional CRM: Toward a Conceptual Framework for Social CRM Practices, Harnessing the Power of Social Media and Web Analytics, IGI Global, Chapter 5:103-131.

4 Trainor, K.J., Andzulis, J.M., Rapp, A. and Agnihotri, R. 2014. Social media technology usage and customer relationship performance: A capabilities-based examination of social CRM, Journal of Business Research, 67(6):1201-1208.

5 Reinhold, O. and Alt, R. 2012. Social Customer Relationship Management: State of the Art and Learnings from Current Projects. In Bled eConference, 155-169.

Image:

Flickr.com

 

Big Data for Small Retailers – Is it Doable?

Do Big Data (BD) for small retailers offer an opportunity to compete with the big retailers or is it too much trouble? One of the fall outs of the digitization of business is the massive amount of data that are everywhere. Every time a customer makes a purchase online or registers online, data is generated. The data can potentially tell you almost everything about consumers. Retailers that sort, analyse and interpret BD can add value for customers and so increase their shopping experience.

Surely retailers should take advantage of BD since it contains captured detailed information that probably was overlooked in the past. However, to get the most out of BD, retailers need to be innovative. The promise of new revenues, customers, and new businesses with BD will require development and investment in teams and technology 1. But first let’s have a look at what BD is all about…

What is big data?

Big data is a term that primarily describes data sets that are so large, unstructured, and complex that it requires advanced and unique technologies to store, manage, analyse, and visualize 2. Therefore, big data represents the data sets that cannot be perceived, acquired, managed, and processed by traditional IT and software/hardware tools within a tolerable time 3. Compared with traditional data sets (small data), big data typically includes masses of unstructured data that need more real-time analysis, according to Chen, Mao, and Liu, (2014).

Where can retailers find Big Data? Rajdeep Nair responds as follows on Quora: “Data is everywhere… it can be purchase data or images uploaded by you on the social media site or data sent by mission sent to Mars by NASA. Everything that is there on the internet and company or an organisation’s confidential data stored on the server. Mostly  data is stored on the server, the technology of which is improving and evolving rapidly.”

However, a good place for small retailers to find “Big Data” is on their own systems. Have you ever analysed your own data sets before?

What retailers can do with Big Data

According to Russell Walker 1, firms that are first movers in leveraging BD have great advantages because they develop innovative insights about customers and markets. These insights can transform services, and even business models. Bernard Marr, contributing to Forbes declared Big Data as “A game changer in the retail sector”.

Bernard notes that Big Data analytics is now being applied at every stage of the retail process. Says Bernard: “BD is used to understand what the popular products will be by predicting trends, forecasting where the demand will be for those products, and optimizing pricing for a competitive edge.”  Moreover helps BD retailers to identify the customers that are likely to be interested in their products and works out the best way to approach them. It also to help them making the sale and working out what next to sell them.

Alex Woodie writing a piece in Datanami.com suggests there are 9 ways retailers are using big data technology to create an advantage in the retail sector.

The advantages of Big Data to retailers

  1. Recommendation Engines – by training machine learning models on historical data, the savvy retailer can generate accurate recommendations before the customer leaves the Web page.
  2. Customer 360 – customers expect companies to anticipate their needs, to have the products they want on-hand. Also to communicate with them in real time (via social media), and to adapt to their needs as they change. In the cutthroat world of retail, developing a customer 360 system using Big Data may be a matter of survival.
  3. Market Basket Analysis – is a standard technique used by merchandisers to figure out which groups, or baskets, or products customers are more likely to purchase together. It’s a well-understood business processes, but now it’s being automated with the help of BD.
  4. Path to Purchase – analyzing how a customer came to make a purchase, or the path to purchase, is another way big data technology is making a mark in retail.
  5. Social Listening for Trend Forecasting – platforms like Hadoop were designed to facilitate the handling and analysis of large amounts of unstructured data, such as Facebook posts.
  6. Price Optimization – setting the right price requires knowing what your competitors are charging. Data can be collected electronically using daemons that crawl competitors’ website to get detailed info about product pricing.
  7. Workforce and Energy Optimization – big data technology can deliver benefits on the marketing and merchandising side. As a result it can help big retailers optimize their spending on human capital.
  8. Inventory Optimization – by analysing BD, retailers can plan their seasonality in the shipping algorithms better.
  9. Fraud Detection – retail fraud is a huge problem, accounting for hundreds of billions of lost dollars every year. Retailers have tried every trick in the book to stop fraud, and now they’re turning to big data technology to give them an edge.

Concluding

The narrative about Big Data is more with ‘Big Retailers’ at this moment. However, with smaller retailers adding the online channel to their business, there are ample opportunities for them to use their own data to great effect. Everything else will cost retailers a lot of money. Maybe to start with small data is better for smaller retailers.

Have a look at this video by Tera data corporation more more on Big Data for retailers:

Notes

1 Walker, R., 2015. From big data to big profits: Success with data and analytics, Oxford University Press.

2 Xu, Z., Frankwick, G.L. and Ramirez, E. 2016. Effects of big data analytics and traditional marketing analytics on new product success: A knowledge fusion perspective. Journal of Business Research69(5):1562-1566.

3 Chen, M., Mao, S. and Liu, Y. 2014. Big data: A survey, Mobile Networks and Applications, 19(2):171-209.

Image and video

Pixabay

Tera Data Corporation