Tag Archives: marketing automation

Marketing Automation is enabled by Artificial Intelligence, Big Data and Chatbots

“Marketing automation is growing – sizzling fast, announced Michael Jans recently in his blog AgencyRevolution.com. In fact, there are eleven times more B-B companies using marketing automation than were in 2011 (VBInsight). Most visible marketing automation for retail customers are chatbots.

Advancements in artificial intelligence (AI), coupled with the proliferation of messaging apps, are fuelling the development of chatbots.  Artificially intelligent chatbots or conversational agents can be used to automate the interaction between a company and customer.

What is Marketing Automation?

Marketing automation, in general, complements interactive and direct marketing with the help of automation and further on in CRM and email marketing 4. The goal of marketing automation is to target the right customer with the right content 1. To achieve this goal, the optimization of customer data – e.g. name, contact information, transactional data is critical. Consequently customers can be targeted with the right message. Therefore marketing automation allows marketers to respond instantly to identified opportunities in real-time even outside the marketing plan.

This use of marketing intelligence provides valuable management insights to markets, customers and campaigns and leads to enhanced efficiency. Also, this same use of data enables customers to receive personalized, relevant messages and offers at appropriate times. As result of this, customer experience is improved significantly. Indeed, Sarah Burke of Spokal concurs: “Marketing automation is a super effective tool when it’s used to supplement our marketing efforts in an attempt to make the lives of our customers even better”.

However, marketing automation is facilitated by Artificial Intelligence.

Artificial Intelligence

Techopedia defines Artificial intelligence (AI) as an area of computer science that emphasizes the creation of intelligent machines that work and reacts like humans. AI is becoming part of our lives ever more. Today we can ask a computer questions, sit back while semi-autonomous cars negotiate traffic, and use smartphones to translate speech or printed text across most languages. For AI to work properly, the machines or robots needed to be ‘learned’.

Machine learning is the process that offers the data necessary for a machine to learn and adapt when exposed to new data. Nello Cristianini suggests we should think of it as training a machine: “It depends on the other two methods by reading mined data, creating a new algorithm through AI, and then updating current algorithms accordingly to “learn” a new task.”

For most retailers and marketers in the digital economy, the intelligent ‘machines’ of choice are chatbots. However, chatbots are dependent on a host of interconnected and emerging technologies, many of which rely on machine learning and require massive amounts of data 3.

The use of data to enable Marketing Automation

Douw G Steyn, owner of the Bricks2Clicks (this blog) had this to say about Big Data: “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.”

Randy Bean in MITSloan commented on the use of Big Data with AI: “The impact of Big Data goes well beyond simple data and analytics. Big Data and AI in combination are providing a powerful foundation for a rapidly descending wave of heightened innovation and business disruption. While the first wave of Big Data was about speed and flexibility, it appears that the next wave of big data will be all about leveraging the power of AI and machine learning to deliver business value at scale.“

Data mining can find the answers to questions that you hadn’t thought to ask yet. What are the patterns? Which statistics are the most surprising? What is the correlation between A and B? (upfrontanalytics.com).

“Intelligent machines need to collect data – often personal data – in order to work. This simple fact potentially turns them into surveillance devices: they know our location, our browsing history and our social networks. Can we decide who has access, what use can be made of the data, or whether the data gets deleted for ever? If the answer is no, then we don’t have control” says Nello Cristianini in the New Scientist.

Chatbots as interactive conversational platforms

By definition, a chatbot is a computer program that responds to natural language text and/or to voice inputs in a human like manner 2. Chatbots can run on local computers and phones, though most of the time they are accessed through the internet (Chatbots.org). Moreover, the effectiveness of Chatbots is depended on the quality of the source data and how well they are programmed. They are after all robots! And robots need to be learned…

Once a customer starts to interact with a chatbot, the chatbot’s software identifies the customer. The chatbot will then have the demographic information of the customer, her purchasing history – such as what products she’d purchased most frequently, what time of the year she does most of her shopping, and when last did she purchased? The scope and depth of information can be never-ending.

The  of a typical conversation between a chatbot and a retail client (image: Chatbotsnewsdaily)

Eric Samson writing in Entrepreneur.com mentioned 7 benefits using chatbots as marketing tools

  1. Customer service – by providing the chatbot option for customers, you will lower the stress of dealing with customer service and increase customer satisfaction with your brand.
  2. Consumer analysis – chatbots can play a large role analysing customer data, and optimizing sales and marketing strategies in light of this analysis.
  3. Personalized ads – another chatbot strategy that’s proven to be successful is the creation of personalized ads.
  4. Proactive customer interaction – chatbots are ideal for “reach out” initiatives. To do this, the accompanying action should be something small, like inquiring whether or not the customer needs assistance.
  5. Site feedback – chatbots are great for reaching out to customers via simple questions and the gathering of feedback. This strategy is useful, especially for website optimization.
  6. Lead-nurturing – using the information that chatbots collect about a customer, you can create customized messaging that guides the consumer along his or her “buyer’s journey,” ensuring movement in the right direction that achieves higher conversion rates.
  7. Maintain a presence on a messenger act via a chatbot – by maintaining a presence on a messenger app via a chatbot, you can save money while simultaneously remaining available for your customers 24 hours a day.

According to Chatbot Conference, the 3 main disadvantages of chatbots are:

  1. Too many functions – most of developers strive to create a universal chatbot that will become a fully-fledged assistant to user. But in practice functional bots turn out not to cope with the majority of queries.
  2. Primitive algorithms – AI chatbots are now considered the best as they can respond depending on the situation and context. However, complex algorithms is required for this purpose. Meanwhile, only IT giants and few developers possess such powerful technological base.
  3. Complex interface – talking to a bot implies talking in a chat, meaning that a user will have to write a lot. And in case a bot cannot understand the user’s request, he will have to write even more. It takes time to find out which commands a bot can respond to correctly, and which questions are better to avoid. Thus, talking to a chatbot does not save time in the majority of cases.

Concluding

With Big Data, Artificial Intelligence and Chatbots there aren’t a clear ‘pecking order’. The Upfront Analytics Team explain it as such: “Data mining, artificial intelligence, and machine learning are so intertwined that it’s difficult to establish a ranking or hierarchy between the three. Instead, they’re involved in symbiotic relationships by which a combination of methods can be used to produce more accurate results.”

The speed at which technology is moving forward – “software is developing software” and “machines are building machines” an affordable, practical usable chatbot for customer care and marketing is not far away…

Read also:

  1. Predictive Analytics helps Retailers to make sense of Big Data
  2. Chatbots in Retailing – a Fact or a Fad?

Notes

1 Mattila, J. 2016. Customer experience management in digital channels with marketing automation, Master Thesis, University of Oulu, Department of Information Processing Science.

2 D’Haro, L.F. and Lue, L. 2016. An Online Platform for Crowd-sourcing Data from Interactions with Chatbots. Proceedings of WOCHAT, IVA.

3 Etlinger, S. 2017. The conversational business: How chatbots will reshape digital experiences, Altimeter.

4 Sandell, N. 2016. Marketing automation supporting sales, Master’s Thesis, University of Jyväskylä.

Image

Pixabay

 

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