Finding strong members for your team is one of the most important skills needed to succeed and a recent Harvard Business Review article, “21st Century Talent Spotting” by Claudio Fernandez-Araoz, provides some strong insights on how to optimize your talent search. With skills and competencies now the key to finding employees, rather than past experience, you must become skilled at judging potential. This situation is exacerbated by the rapidly changing nature of the tech and game spaces, what worked yesterday are not necessarily the skills you need today.
In the last millennium, workers were selected for physical attributes which readily translated into higher success at physical labor, from building a canal to fighting a war. Business then evolved to judge candidates on intelligence, experience and past performance. Much work was standardized, so if you were looking for an engineer or an accountant or a CEO, you would find somebody who has already succeeded in such a role and there was a high likelihood they would replicate this success. Then hiring evolved to the competency model, which stipulated that managers (and other workers) be evaluated on specific characteristics and skills that would help predict outstanding performance in the roles for which they were being hired. Hiring managers would decompose jobs into competencies and look for candidates with the best combination of these skills. Continue reading
When I recently updated my OpenTable app, I noticed they incorporated a partnership with Uber in which you can request a car when looking at an upcoming reservation and the car would already know your destination. This partnership between Uber and OpenTable is a great example of strategic thinking by both companies. I wanted to comment on it as I think all companies can learn some key lessons from the initiative.
I recently read a very interesting post, How Machine Learning can Improve Customer Interaction, that does a great job of listing different ways you can leverage machine learning to communicate better with your customers. The ideas include:
- A personalized approach when you visit a website. When you are on an e-commerce site or using a search engine, the host collects rich information on your behavior. Machine learning analyzes the data and transforms the website into something geared to the individual customer. Machine learning then will control what you see, what appears in a search bar, how the site communicates with you, to best meet your individual needs.
- Making recommendations. Making recommendations relevant for the user was one of the first major consumer applications of machine learning. Virtually everyone has experienced Amazon’s recommendations, when you make a purchase it recommends products likely to resonate (and almost everyone has taken advantage of these recommendations). Automated personalization with machine learning takes information about the shopper, refines those recommendations and tailors them specifically to the individual shopper. As the article points out, “it is like having a salesperson with the customer the whole time, pointing out what products he or she thinks are right up the customer’s alley.”
Given the importance of working with platforms and intermediaries to tech and game companies, managing the relationships with the platform becomes crucial to your success. A Harvard Business Review article earlier this year, “Mastering the Intermediaries” by Benjamin Edelman, lays out a strategic framework for optimizing these relationships.
Regardless of your business, if you are not a platform you probably rely on one or another type of intermediary for your success. Airlines and hotels are at the mercy of Kayak, Orbitz, Priceline and other platforms. Game companies rely on Facebook, Google and Apple for their access to customers. Small restaurants use Seamless or Foodler to reach hungry customers. Manufacturers must sell through Amazon to gain access to a large market. Moreover, almost every retailer looks to Google to refer customers.
These intermediaries provide valuable benefits (hence why everyone works with them) but they can also capture a disproportionate share of the value a company creates. These costs, also, do not dissipate through competition as most markets usually only have one or two significant platforms (mobile phones, anyone). Thus, companies feel they have no choice but to accept the fees and rules the platforms institute. Edelman’s article, however, shows strategies for recapturing some of the value companies are creating and protecting yourself from abuse by the platform. Continue reading
In a time when people are very cynical about businesses, earning the trust of your customers or players is increasingly important. Trust gives validity to your marketing messages, allowing you to communicate with your customers, inform them of new products and features and thus increase their long-term lifetime value (LTV). Conversely, if customers do not trust you, there is very little you can do to retain them or reactivate them other than just compete on price.
A recent article, “How Do You Know if a brand is TRUSTworthy?!,” polled readers to list what makes a brand trustworthy. The responses are very enlightening in terms of building trust for your company or product:
- Create social media content that is not simply marketing. By creating useful content, not just sales collateral, you are building trust with your customers.
- Handle negativity well. Rather than ignore or avoid problems, get in front of them and clean up the issue.
- Do not worry about simply getting a large number of followers, focus on getting followers who are truly engaged with your product or game.