Why You Shouldn’t Track Only Online Customers

                          Online shopping is the ‘in’ thing today. The online business is booming & giving impressive growth numbers. Naturally, companies have identified the utility of online business presence & have acted upon it by creating strategies that place paramount focus on this channel. Keeping all that in mind, online shopping is still tiny compared to the brick & mortar channel. Sure, online is winning the fight, but the battle is yet to be won. The numbers given in this article from WSJ proves as a sufficient illustration. And it’s going stay this way for a significant amount of time. Who knows, we may even see a new twist in the paradigm. My point being, marketers need to look beyond all the hoopla & avoid the catastrophic mistake of ignoring their offline customers. They’re still going to be your main source of revenue for years to come.

Source Link: http://on.wsj.com/N7N49i

Brick & mortar retailers are increasingly becoming aware of the threat from E-commerce & are trying some tricks of their own. There are a few fundamental differences between online customers & offline customers. Online customers have many choices, all of them at the tip of their fingers. They face many distractions than a brick & mortar customer, too. While on web, a customer can be easily distracted by an impressive advertisement from another store. Moreover, switching costs for an online customer are next to nothing. He is likely to get the same information on every other online store & since the overall shopping experience is roughly identical everywhere, it becomes very difficult to retain an online customer.   On the other hand, offline brick & mortar customers are far less likely to switch outlets. This is because all the outlets of the brick & mortar variety are not that easily accessible to everybody. More importantly, it is very difficult for the online stores to compete with their brick & mortar counterparts in terms of providing diverse shopping experiences. The sheer range of shopping experiences (combination of tangible & intangible aspects) that a physical store is capable of providing gives it a vantage point for retaining customers.  

Hence, we can conclude that offline customers are more likely to remain loyal to an outlet. So, it makes a lot of sense in taking efforts to engage & retain the brick & mortar customers. Consider this on the backdrop of huge sales numbers in physical retail, and any reasonable marketer will direct at least some attention to his offline customers.

One more reason for our rejuvenated interest in tracking offline customers is simply because now you can do it. Technology is available that enables a marketer to track physical customers with very little expenses. I believe the specific industry is called ‘In-Store Analytics’. With the advances in communication technologies (especially wireless communications like Beacon & Wifi), it is now possible to track a really wide range of activities of the physical customers (You may visit our blogs – Tracking Customer Activities (A Process-based Approach) & The ‘Geeky Side’ (Technology) of Customer Engagement). The advantages of using In-Store Analytics & Intelligence solutions for tracking offline customers cannot be emphasized enough. The share of brick & mortar retail in the total retail sales is too large to stop innovating in that area.           

Decoding the Customer Behavior – Numbers or Intuition?

Watched (actually re-watched) a movie recently. The movie was Moneyball, released in 2011, starring Brad Pitt. This got me thinking about one of the oldest & most discussed topics in business – Number-based decision-making vs Intuition-based decision-making.  

Let me first summarize the movie for those who haven’t seen it yet. In the movie, Brad Pitt is a general manager of a baseball team with very low budget. With his best players being poached by other bigger clubs, he realizes that the game is ‘unfair’ & optimal solution won’t be obtained by conventional means. So, he adopts an entirely new approach of scouting players on purely numeric basis, thereby assembling a team to satisfy the statistically calculated numerical requirements of the team. The approach proves to be a successful one & we witness a remarkable turnaround in the fortunes of his team. Over the course of the movie, before the success, we see many senior personalities in baseball warning him not to ditch the traditional methods of recruiting players based on a scout’s intuition & experience of the game. 

This got me thinking about one of the most fundamental debates in business – numbers vs intuition. In this article, let us have one more look at both the approaches from our perspective of decoding the customer’s buying & loyalty-related behavior. Let me state at the beginning itself that strong cases can be built for both approaches. There is no single approach that is universally applicable at all times.

In the number-intensive approach, most of the decisions are made purely on the basis of numerical data. Thought process of Billy Beane, the character of Brad Pitt in movie Moneyball can be used as a quintessential illustration of this approach. In the context of understanding customer behavior, customer data for various customer activities needs to be collected (you may visit our article on this topic here).  Then, we have to identify the trends & patterns that will guide us in the decision-making. This data can act as a solid backup to support your decisions. This is especially true if the decision backfires later on. The analyzed data proves to be of a great help when explaining the decisions taken to the stakeholders. Generally, such trends, patterns, percentages, ratios etc. are compared with the past calculations & technically analyzed at great length. Hence, it does tend to result in informed decisions. However, there are some downsides to this approach. Most of the times (especially when end-customers are involved) data is not collected for the entire population. Only sample data is collected which is a very small subset of the entire population. These samples are then extrapolated to get the picture of entire population. Thus, in effect, the preferences & choices of few people are applied to entire population. This could result in mismatch with a lot of expectations. Furthermore, it is impossible to measure every customer activity. Thus, numeric data may not be present for many important parameters, such as perceptual mapping of the product in consumer’s mind, tendency of the customer towards brand advocacy etc. Hence, number-intensive approach is useful when you want to measure tangible things & for existing products. 

In Intuition-based decision making, decisions are taken on the basis of the marketer’s knowledge of the industry. So, domain expertise of the decision-making team takes a prime importance. As discussed above, numerical extrapolation doesn’t always give a clear picture of the diversity of preferences. Furthermore, only market experts can get the hang of the complex social & emotional dynamics as well as other unusual market specific factors. This becomes particularly apparent when products/services for which customer behavior is to be gauged are of novel nature. In case of disruptive products & technologies, there’s really no alternative to intuition, since past data is either absent or inapplicable. Such gut-feeling based decisions are less mechanical & they tend to foster creative thinking, which is sometimes desperately required in customer engagement domain. As creative & righteous as this approach may seem, it has its obvious downsides. In intuition-based decision making, it becomes very difficult to explain the underlying basis of decisions since there isn’t really a scientific basis for decisions. If such decisions don’t work for whatever reason, it becomes troublesome to justify them. Also, objectivity of the decision-maker is a crucial aspect, without which such decisions may be subjected to personal whims or preferences of the decision-maker.

Now, if you were to implement a CEM solution, how should you select a platform that takes care of both the scenarios? You should always go for the platform which will give you all the data, trends, patterns, graphs & summarized dashboards plus other analysis tools to suggest the possible decisions. On the other hand, the chosen platform should allow for flexible decision making via manual interventions & highly customizable criteria.  So, while choosing a platform, ideally you should look for thorough numerical assistance (via dashboards, graphs etc.) as well as flexibility for customized decision-making with manual interventions. At Birdvision, we have developed our CEM platform on the foundations of similar thinking, handing over the control of the wheel to the user. By the way, the debate of Numbers vs Intuition still goes on. Do share your thoughts with us to add to this debate.  

Amazon Firefly – A Great Alternative to Product Tagging?

Loyalty & Engagement market is evolving at a great pace. Naturally, this process of evolution has had a head-on impact on the scope of the market. Loyalty & Engagement programs are no longer designed only for end-consumers, but loyalty is solicited from your distribution channel partners too. There weren’t any doubts ever on the impact of the supply chain & distribution channel partners (Distributors, Wholesalers, Retailers etc.) on end-sales of the products. However, somehow marketers weren’t looking beyond discounts & service support to gain loyalty from their channel partners. Even today, most of the distribution chains in the consumer electronics industry depend on these two tactics to keep their channel partners loyal. But, this does not solve the broader problem. Even if we assume that they manage to keep their channel partners loyal, they do not really promote sales. The best way to drive sales within the distribution channel is by turning the channel partners into your ‘extended sales force’.

Traditional discounts are discontinuous. They generally occur once per bulk purchase transaction by channel partner. If we can somehow find a way to link each & every primary, secondary & of course tertiary sale (which is generally the end-sale to the customer) to give incentives to channel partners, it would be great engagement method. How to do that? Two words – product tagging.

Product tagging is perhaps the only method of tracking the sale events of a product through various levels of the distribution chain. Uniquely coding the products to account for each tier in the chain seems to do the trick. Here’s the catch – Product tagging is extremely difficult in real-life once the product comes out of the factory automation environment. And in actual practice most of the tagging has to be done outside these automated environments – in the warehouses or shipping bays. It tends to become exponentially difficult when there are multiple tiers of codes (for each tier in the distribution chain) or there are many SKUs in the company’s assortment. Lack of skilled labor in the warehouses & packaging departments just compounds the pain. 

Here, I’ll try to propose a highly ambitious solution to this tagging problem. And the solution is – don’t tag the products! Before you begin to question my mental condition, hear out the last piece of the puzzle: Amazon’s Firefly technology. Amazon has been working on real-life object recognition through intelligent image & sound processing for better part of a decade now. As you may be aware, it has very recently launched its own phone, the Amazon Fire phone which contains this breakthrough feature called Amazon Firefly. Amazon Firefly’s premise is that it claims to be leaps & bounds ahead of other technologies in the field of object recognition. You just have to press the ‘Firefly button’ provided on the Fire phone & it will turn on its sensors (camera, microphone, GPS) to recognize whatever object you are looking at (image recognition) or  listening to (sound recognition) or a mixture of both. Thus product tag (unique code pasted on the product packaging) is out of the picture since the mere event of scanning & recognizing the product through the Firefly feature can be used to identify the product. However, we have to make a major assumption here. We’ll assume that sale has happened even if customer just scans the products, regardless of tracing the actual sale. Still, the next thing that I’m going to point out may very well be the workaround for this issue. Amazon has opened the SDKs for the Firefly technology for developers to build their applications around it. Of course there is going to some usage fee involved, but developers will have the power to add unprecedented level of intelligence to their applications. 

Applying this to our context of product tagging, we may build an application which will recognize the unique serial number or barcode or QR code present on the product to establish the proof of purchase. And these serial numbers can very well be added to the product in the factory automated environment. There is another way which could bypass product tagging altogether if we force the customers & channel partners to complete the purchase transaction only through the portal or application specified by us.

We have to make another assumption – availability of Fire phone on a mass scale. Only time will tell validity of this assumption. For now, we can do nothing but get mesmerized by the technology & hold our breath for it to solve the painful product tagging problem.