George Olsen talks about the importance of personas as a valuable design tool in driving strategic and tactical level details.  

Personas are fictitious characters that are created to represent different product user types and to aid tactical and strategic level decisioning. Typically, ad agencies have relied on qualitative methods such as interviews, focused group discussions, existing literature to develop a typical character sketch. However, a well designed persona is one which not only suffices an ad agency’s need but also addresses the interests of other stakeholders including marketing, sales, finance and HR teams.

Recently, our client, a financial services firm, wanted to understand the attitude and behavior of their users. They wanted to strengthen their brand architecture and develop the right kind of messaging for target audience. We expanded on our market segmentation approach and used the granular primary research data, company’s transaction data and third party segmentation schema (Claritas) data to do develop personas in a bottoms-up fashion. The data driven approach of building personas leveraged internal data, survey data, and a third party segmentation schema (Claritas P$YCLE). 
We followed a four step approach to develop the personas:

1.       Conducted a survey to capture the attitude and behavior of respondents towards financial issues and planning

2.       Used a statistical technique called principal component analysis to reduce some 40 attitudinal and behavioral variables captured from the survey to two dimensions – expectation from the service provider and level of financial anxiety. We used cluster analysis to classify the respondent pool on these dimensions.

3.       Built personas by mapping the clusters to the Claritas segments so as to capture information around media preferences and lifestyle behaviors. We enriched the personas with survey information including demographic indicators, behavior towards financial service providers, financial anxiety, as well as Claritas segments that helped highlight media, lifestyle, and income-producing asset ownership traits

4.       Performed a “day in life” analysis to understand how a typical day for a persona would look like in his or her diary. This analysis explored the various lifestyle and media touch points which can be used for tactical marketing initiatives

Our approach to leveraging rapid market segmentation helped our client not only to understand the segments on the basis of attitudinal dimensions but also to appreciate the strategic and tactical initiatives that can be achieved with robust data driven personas.  This level of understanding of their customers helped them improve their segment specific marketing messaging and customizing the store experience for each segment.

As the US and the world economies encounter a downturn and firms look to scale back, Marketing is often one of the first places to face budget cuts.  Forrester reports that many companies expect to cut their marketing budgets by 3%.  But how do you maintain or grow your customer base and revenues when consumers are spending less and your message isn’t getting into the marketplace as loudly?

We think the use of online coupons deserves a harder look.  Emailing your customers and prospects with newsletters, product updates, and coupons is certainly nothing new, but it’s now well-positioned for even greater success:

• Companies are getting good at it. After dabbling in techniques like SEM and direct email, firms have gotten better at driving profitable growth from these methods, and many are increasing their focus on online advertising as a cheaper way to spend their marketing dollars. 
• Consumers want more of it. During these uncertain times, consumers plan to increase their use of coupons to save some money.  Sending these options straight to their inbox or mobile phone accomplishes that goal and positions you as a preferred provider.
• Consumers who use it are attractive prospects. Compared with consumers who only use offline coupons, Forrester reports that users of online coupon tend to have higher incomes, shop online, like to try new products, and influence peers.  Younger consumers also use coupons, and they can be a good avenue to get the word out about your product.
• More data is available to help you win at it. More firms sell marketing lists (or can help you run campaigns to get new lists), segmentation data helps you understand consumers’ preferences and desires, and syndicated data helps you understand purchase behavior.  Combining this data gives you incredible insight into consumers to tailor unique marketing messages.

You don’t just want to throw promotion dollars at existing customers to give them discounts on things they were already going to buy; rather, you likely want to use those dollars to deliver positive returns and achieve business goals – such as acquiring new customers, increasing market share, or increasing wallet share.  Doing this requires targeting offers to customers based on their stage of the customer life cycle:

1. Acquire. Coupons can be a good tool to help consumers overcome the risk associated with trying a new product; if a new product is cheaper than the one they normally use, the savings might be worth trying.  You can use them to attract entirely new customers to your firm, or to get your existing customers to try a new product line.  Targeting early adopters can also help generate buzz, as they will influence friends and family to buy the product as well.
2. Grow/Stimulate. Once you’ve acquired a customer, you want them to maintain or increase their purchases.  Two ways of stimulating usage are encouraging them to try a different variety (e.g., color, size, flavor) or showing them new uses for the same product (e.g., using Q-tips for craft projects in addition to hygiene).  In this stage, the focus should be on the marketing message, the coupon being used to help seal the deal and drive the customer to the store.
3. Manage. In this stage, your customers are steady-state users, and couponing may not be required to retain them. However, these consumers present a good opportunity to test new offers on an already loyal customer base and measure the response before using them on the general public.  You might test them using different demographics, layout, or wording, perhaps even running controlled experiments to determine which of two offers is more effective.  We’ve done some research on the use of Behavioral Economics to improve offer design, which might be helpful in performing this testing.
4. Reclaim. If customers reduce their consumption or begin to try competitors’ products, you can use targeted offers to reintroduce your product and retain them as customers.  However, depending on their needs and your product pipeline, you may otherwise opt to move back to the beginning of the life cycle and acquire them as customers of another of your products.

This strategy requires a high level of customer insight to understand preferences and stages in the life cycle.  You can gain this insight by applying segmentation schemes to your lists of customers and prospects, and by analyzing your customers’ history of purchases and coupon redemption.  Applying a rigorous testing approach will help you identify the most effective offers for each customer and stage.

Applying this framework to understanding your customers and targeting coupons will deliver several benefits, including:

1. Strong ROI potential.  Campaigns that are more effective and lower-cost, targeted at attractive customers, have a stronger potential to deliver a positive ROI.
2. Better data to analyze results. Results of online campaigns are easier to track and measure than traditional campaigns, particularly if your coupons lead customers to purchase from your own website.  Analyzing results from campaigns that involve multiple partners may require a different approach, as Vishal outlined in his earlier post on trade promotions.
3. Better customer relationships. You can use the insight you’ve gained about your customers’ behaviors, preferences, and purchase history to continually develop targeted offers.  This level of personalization will help you deliver the right offers to the right customers at the right time, and ensure that your promotion dollars are spent most effectively.

A recent article in the New York Times discusses the impact of price on the perceived effectiveness of drugs.  The article describes an experiment where two groups of patients receive a placebo drug that they are told is a pain reliever, but the groups are told different price points.  After taking the placebo and receiving electric shocks, more people (85%) who were told it cost $2.50 reported pain relief than those who were told it cost only $0.10 (61%).  While the placebo effect is well-documented, this experiment highlights an important application to business – that a product’s price can be an effective marketing lever that can directly impact its effectiveness and value.

This is not the first time that cues such as pricing and packaging have been applied to marketing.  We recently collaborated with Professor Ariely (also quoted in the article) to explore the impact of applying behavioral economics principles to online marketing strategies.  One of the concepts we discussed in the resulting paper, is “Framing,” and we explored how consumers evaluate their options on relative terms, and make purchase decisions based on the cues given to them.  In the paper, we highlight the example of a magazine publisher who was able to steer consumers toward a higher-cost option simply by presenting a lower-cost one.  Even though no one chose the lower-cost option, it was an effective cue in that it showed the relative value of the higher-cost one.  In the drug experiment, price was the cue, and the higher price led consumers to find it a more effective (and valuable) product.

In our market segmentation work, we have found that different consumer segments require different value propositions, and that marketing messages need to emphasize factors such as features or pricing to appeal to their target markets.  Many generic, store-brand products are actually the same as the name-brand products, but are packaged differently and sold at a lower price to appeal to a different consumer segment.  The drug experiment highlights the same concept – and 61% of the patients who thought it was a cheap drug still reported that the product was effective in relieving their pain.

In developing marketing strategies, it is important to carefully consider the market segments you are targeting, along with the value drivers for each.  Understanding these drivers allows you to apply behavioral economics principles to maximize ROI through optimal pricing and product framing for each segment.

A set of whitepapers for the executive who wants to leverage the data to make smart marketing investments:

1. Identifying attractive markets and understanding your customers
2. Increasing online sales
3. Focusing on profitable distribution partners
4. Improve customer experience through call center data
5. Retaining your customers

We were working for a large Fortune 500 company to assess the performance of its sales team’s incentive program. A two tier incentive structure was in place for the sales force.
·        The incentive was directly proportional to the revenue generated by the salesperson
·        The salesperson generating revenue beyond a certain cutoff was given extra perks and monetary rewards
Prima facie this incentive structure made sense but when we analyzed it carefully, an array of systemic problems was observed. We mention few of the issues with potential ideas to tackle them
1)      Setting and maintaining goals – The incentive revenue cutoffs were predefined, static and the senior stakeholders had the power to override them. The cutoffs and tier allocations were not reviewed on a regular basis, making the tiers passive for the candidates who are performing well over a period of time. 
The key is to better understand the performance drivers of the sales force by  defining and measuring appropriate metrics  (using correlations, principle components, and factor analysis). Appropriately segmenting the sales force, defining the segment cutoffs using historical data and then reviewing them on a periodic basis is critical to achieve a better return from an incentive program.
 

2)      Quality Vs. Quantity of Money - Sales force were rewarded based on the volume (revenue) of the business and not the quality of the business (margins). Targeting the wrong prospects by the sales representatives sometimes led to value negative customers.
Using lifetime value calculation (LTV) of customers instead of absolute number of customers or amount of revenue, as the performance metric will solve this problem. Most organizations do understand the theory but do not use the metric, because calculating customer lifetime value is tricky and the data is not always available to do so accurately. In our opinion, it is better to have an incomplete understanding of the lifetime value (using averages and proxies for certain aggregated costs) rather than not making an attempt to calculate and use the metric. A flawed metric is better than a wrong metric.
 

3)      Poor and inadequate data - Data to track performance and understand the drivers of success for sales representatives was not readily available. The data was collected was mostly in standalone excel sheets. They were manually reported and coded making it difficult to link the independent tables.
A culture of measurement fosters investment in better data capturing systems. As analytics is used to calibrate the incentive structures on periodic basis, investment in centralized systems to standardize the data collection process will reduce analysis cycle time and increase accuracy of the analysis.

An integrated view of the incentive program helps in incentivizing the right people for the right reasons with the right benefits. Analytics is part of the answer. However, as emphasized by most of our projects, we believe that a sustainable solution is a combination of a robust understanding of business processes, technology infrastructure and analytical techniques.
 

A recent article in WSJ talks about how offline segmentation schemes and data is being used for online targeting of advertisements. The sidebar of the article mentions how Acxiom executes on this strategy

1. Acxiom has accumulated a database of about 133 million households and divided it into 70 demographic and lifestyle clusters based on information available from public sources.

2. A person gives one of Acxiom’s Web partners his address by buying something, filling out a survey or completing a contest form on one of the sites.

3. In an eyeblink, Acxiom checks the address against its database and places a “cookie,” or small piece of tracking software, embedded with a code for that person’s demographic and behavioral cluster on his computer hard drive.

4. When the person visits an Acxiom partner site in the future, Acxiom can use that code to determine which ads to show.

5. Through another cookie, Acxiom tracks what consumers do on partner Web sites.

At a client engagement we also have utilized a similar strategy (however without using any personally identifiable information like email address) to understand how segments of customers consume content on a website (see image below). This information is used to develop and personalize content on the website and can also inform site layout and design.

What we are witnessing is that companies are trying to bridge the worlds of marketing and web analytics. As we have previously mentioned, third party segmentation schemes which are so pervasive in the marketing world will increasingly become the translation layer between the two worlds.

Jim Novo, who authors an insightful marketing blog, rightly identifies that PRIZM clusters (or other geo-demographic segmentation systems) are not as predictive as a behavioral data for desired ‘action’ in the online world.

e-commerce folks are usually looking for behavior from customers, and the fact demographics are not generally predictive of behavior by themselves

Segmentation and targeting are different and PRIZM is fundamentally not a targeting tool. Even in the world of direct mail where rich behavioral data from website is not available; it is rarely used as the sole targeting criterion.

However, geo-demographic segmentation systems like PRIZM, have some benefits for which web analysts should consider using them. Here are four reasons for which we have used PRIZM in an online setting:

1. Customer data is available
When customers login to your website and it is possible to link them to their PRIZM code, you have one more variable to put into your targeting models and an additional dimension of information on your customer.

2. Tie back to non-online world
In most organizations, web analytics is another marketing silo, and senior executives do not yet understand how to relate their online and offline customers/visitors with their media buying strategy, direct mail strategy etc.. A segmentation scheme like PRIZM plays the role of a standard translation engine for the various marketing organizations to describe a customer. Identifying your online visitors using PRIZM helps your marketing department create a holistic view of the customer.

3. Hypotheses to identify content gaps
If you are a content-based site, then having PRIZM segment of your visitors associated with its rich detail on media consumption and lifestyle interests, will help develop hypotheses on the existing content gaps on the website. You will need to augment it with good market research and do rigorous testing to identify what really works.

4. Monetizing the site
Advertisers understand PRIZM – so if you have advertising inventory, then you should consider segmenting the visitors based on it.

PS: PRIZM is one of the major “geo-demographic segmentation” schemes available in the market and we have used the two terms interchangeably in this post

A wireless service provider wants to determine where it should open new stores to attract customers. A paper products company wants to determine whether it is setting the right quotas for its sales people responsible for generating business within their geographies

Companies are often interested in determining the potential size of their market in a particular geography or for a specific product to better manage their sales, distribution and marketing resources. This market sizing problem broadly falls into two categories: whether the customer is a business or a consumer.

The analytical approach to determine addressable markets happens to be very similar. It starts with identifying a very rich data source for the universe of customers, and then applying a layer of filters (e.g. companies with >100 employees, or families with children) based on the specific business needs, to define the target market. This is followed by a estimating the amount the target customer will spend on the service/product – to calculate the potential market size.

Here are two papers which clearly articulate the analytics process, and are a must read before you start any market sizing activity. The first one is for those who sell to businesses and the second one is for the consumer market.

Heinz recently reported a very successful year driven in large parts by its pricing strategy. Increasing prices and simultaneously gaining market share is the holy grail of Consumer Packaged Goods (CPG) companies. A 2005 report from GMA, Nielson and McKinsey identifies some of the salient points around sales, pricing activities of ‘winning’ companies (which they define as companies who not only increased its pricing compared to its category peers, but grew their segment dollar share at the same time)

Setting Price:

• Manage pricing regionally (and some at the market area, micro-market, or even store level) to reflect local variations in price sensitivity that arise due to differences in consumer preferences, competitive intensity and retailer dynamics.
• Use more price elasticity analysis to set the price and integrate consumer insights into pricing more aggressively
• Tailor brand-pack assortment to the needs of a particular region, channel or store format

Realizing the Pricing Increase:

• Use a profit-based rationale to secure price increases and also combine this tactic with a strong understanding of consumer preferences, shopping behavior, and price elasticity.
• Appoint a single head of pricing who collaborates with top leadership and critical functions on both the pricing strategy and its execution. An essential part of that person’s task is then translating the strategy into sales force guidelines that help avoid conflicts between profit and volume goals.

In short, the winning companies are using analytics to drive their pricing decisions and have gone beyond the simple volume based pricing strategies that is the norm in the industry. Profitability, consumer insight, channel management and price elasticity are all areas which require data analytics capabilities. The end of the ERP implementation cycle in the industry means that companies will start developing predictive analytics capabilities and try to use information and analytics as a sustainable competitive advantage.

Avinash summarizes the interesting insights from the recent Emetrics- the online marketing conference. One graph that particularly caught my attention, from a presentation by Tim Hart of J. Paul Getty Trust, is an analysis to determine content consumption of a website.

The blue bar shows the type of content on the site: Education, Research, Collections etc. The red bar shows the percent of Visits to that content.

To put it another way “what are the large chunks of content on the site, what are visitors to our website looking at”.

I am sure the insights will scream out at you. 86% of the content was being consumed by 23% of the visitors. For 25% of the visitors were looking at 4% of the content (Research).

This analysis helps to set the baseline for content consumption at the highest level and informs about the needs of the online visitor to the website. If your website uses any web analytics tool, it should be pretty simple to create the above graph.